Plot
EDA Plot for each crop data
linear reg for yield VS EHF 95
Abbotsford weekly
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27837 -6474 -1373 4047 41932
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 247624.160 53497.038 4.629 0.00169 **
## Week_1 -2171.531 3826.707 -0.567 0.58596
## Week_2 -2744.458 2644.290 -1.038 0.32968
## Week_3 3641.847 3466.401 1.051 0.32413
## Week_4 3003.179 6048.615 0.497 0.63289
## Week_5 1178.247 3445.783 0.342 0.74121
## Week_6 -8750.445 4915.786 -1.780 0.11294
## Week_7 4885.760 6409.091 0.762 0.46775
## Week_8 5235.628 4971.863 1.053 0.32308
## Week_9 1747.502 4600.510 0.380 0.71394
## Week_10 -3484.455 4713.238 -0.739 0.48086
## Week_11 -7730.497 6721.097 -1.150 0.28329
## Week_12 -5157.226 4302.043 -1.199 0.26491
## Week_13 3554.688 4929.279 0.721 0.49136
## Week_14 2938.131 10286.955 0.286 0.78243
## Week_15 11179.958 7376.340 1.516 0.16808
## Week_16 1.334 3193.296 0.000 0.99968
## Week_17 -3851.450 4653.844 -0.828 0.43190
## Week_18 4466.951 3566.116 1.253 0.24572
## Week_19 3144.828 2232.205 1.409 0.19654
## Week_20 7169.321 4975.559 1.441 0.18758
## Week_21 -1530.657 4360.146 -0.351 0.73461
## Week_22 -3232.952 2740.419 -1.180 0.27200
## Week_23 -2143.645 4251.514 -0.504 0.62771
## Week_24 5438.291 4307.202 1.263 0.24229
## Week_25 -7676.930 5358.130 -1.433 0.18982
## Week_26 777.006 1478.901 0.525 0.61356
## Week_27 7691.774 4315.853 1.782 0.11257
## Week_28 3580.131 4283.071 0.836 0.42748
## Week_29 -1154.881 3714.927 -0.311 0.76384
## Week_30 2083.311 2774.364 0.751 0.47421
## Week_31 5982.369 12198.921 0.490 0.63702
## Week_32 -5687.078 3614.449 -1.573 0.15427
## Week_33 -8240.645 5629.085 -1.464 0.18137
## Week_34 27195.753 9710.787 2.801 0.02318 *
## Week_35 -8417.524 5877.329 -1.432 0.18998
## Week_36 8261.557 6418.785 1.287 0.23405
## Week_37 -1111.867 10587.008 -0.105 0.91894
## Week_38 -3434.407 6234.828 -0.551 0.59678
## Week_39 -773.375 5236.137 -0.148 0.88623
## Week_40 -6421.768 8470.863 -0.758 0.47013
## Week_41 -8203.312 7828.657 -1.048 0.32533
## Week_42 11641.966 6518.586 1.786 0.11193
## Week_43 -12452.499 8075.365 -1.542 0.16164
## Week_44 2689.081 6051.644 0.444 0.66856
## Week_45 -14715.632 9651.161 -1.525 0.16583
## Week_46 16405.115 9062.185 1.810 0.10784
## Week_47 -4234.774 4100.397 -1.033 0.33192
## Week_48 2209.198 5307.865 0.416 0.68820
## Week_49 6830.131 5089.663 1.342 0.21645
## Week_50 -7680.498 5335.802 -1.439 0.18799
## Week_51 -3394.036 3890.915 -0.872 0.40846
## Week_52 2109.363 6764.758 0.312 0.76315
## Week_53 -2308.067 4283.919 -0.539 0.60471
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 36040 on 8 degrees of freedom
## Multiple R-squared: 0.9491, Adjusted R-squared: 0.6122
## F-statistic: 2.817 on 53 and 8 DF, p-value: 0.06071
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4213 -1125 -84 1147 4983
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 41267.00 7396.44 5.579 0.000523 ***
## Week_1 159.50 529.08 0.301 0.770741
## Week_2 -459.92 365.60 -1.258 0.243872
## Week_3 331.46 479.26 0.692 0.508751
## Week_4 490.41 836.27 0.586 0.573763
## Week_5 -86.59 476.41 -0.182 0.860296
## Week_6 -1051.44 679.65 -1.547 0.160443
## Week_7 165.41 886.11 0.187 0.856567
## Week_8 1309.93 687.40 1.906 0.093157 .
## Week_9 -566.49 636.06 -0.891 0.399123
## Week_10 -55.58 651.65 -0.085 0.934121
## Week_11 -710.73 929.25 -0.765 0.466328
## Week_12 -301.10 594.79 -0.506 0.626357
## Week_13 88.47 681.52 0.130 0.899920
## Week_14 942.56 1422.26 0.663 0.526139
## Week_15 838.48 1019.84 0.822 0.434803
## Week_16 -32.46 441.50 -0.074 0.943191
## Week_17 -828.63 643.43 -1.288 0.233808
## Week_18 392.15 493.05 0.795 0.449360
## Week_19 690.71 308.62 2.238 0.055595 .
## Week_20 718.53 687.91 1.045 0.326784
## Week_21 112.44 602.83 0.187 0.856675
## Week_22 -14.73 378.89 -0.039 0.969941
## Week_23 -736.03 587.81 -1.252 0.245879
## Week_24 221.83 595.51 0.373 0.719193
## Week_25 -305.94 740.81 -0.413 0.690462
## Week_26 -271.02 204.47 -1.325 0.221611
## Week_27 1663.55 596.71 2.788 0.023635 *
## Week_28 -404.66 592.17 -0.683 0.513685
## Week_29 108.40 513.62 0.211 0.838130
## Week_30 388.34 383.58 1.012 0.340983
## Week_31 -464.93 1686.61 -0.276 0.789797
## Week_32 -4.64 499.73 -0.009 0.992819
## Week_33 -1009.16 778.27 -1.297 0.230892
## Week_34 2567.53 1342.60 1.912 0.092195 .
## Week_35 -1308.31 812.59 -1.610 0.146055
## Week_36 1224.31 887.45 1.380 0.205048
## Week_37 -470.14 1463.75 -0.321 0.756299
## Week_38 77.30 862.02 0.090 0.930749
## Week_39 24.27 723.94 0.034 0.974080
## Week_40 -432.06 1171.17 -0.369 0.721764
## Week_41 473.49 1082.38 0.437 0.673353
## Week_42 1507.43 901.25 1.673 0.132946
## Week_43 -210.32 1116.49 -0.188 0.855269
## Week_44 -702.37 836.69 -0.839 0.425586
## Week_45 -764.99 1334.36 -0.573 0.582193
## Week_46 1168.18 1252.93 0.932 0.378430
## Week_47 -548.78 566.92 -0.968 0.361390
## Week_48 768.53 733.86 1.047 0.325590
## Week_49 169.41 703.69 0.241 0.815807
## Week_50 -489.42 737.72 -0.663 0.525710
## Week_51 -770.43 537.95 -1.432 0.189992
## Week_52 234.75 935.29 0.251 0.808147
## Week_53 -289.59 592.29 -0.489 0.638006
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4983 on 8 degrees of freedom
## Multiple R-squared: 0.9163, Adjusted R-squared: 0.3614
## F-statistic: 1.651 on 53 and 8 DF, p-value: 0.231
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5994 -1963 -161 1272 10520
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 100208.28 12862.34 7.791 5.28e-05 ***
## Week_1 70.66 920.06 0.077 0.9407
## Week_2 -280.53 635.77 -0.441 0.6707
## Week_3 1157.06 833.43 1.388 0.2025
## Week_4 -113.07 1454.27 -0.078 0.9399
## Week_5 -179.41 828.47 -0.217 0.8340
## Week_6 -1901.37 1181.91 -1.609 0.1463
## Week_7 878.86 1540.94 0.570 0.5841
## Week_8 1843.94 1195.39 1.543 0.1615
## Week_9 -1332.39 1106.10 -1.205 0.2628
## Week_10 1049.61 1133.21 0.926 0.3814
## Week_11 -2306.89 1615.96 -1.428 0.1913
## Week_12 -948.67 1034.34 -0.917 0.3859
## Week_13 697.73 1185.15 0.589 0.5723
## Week_14 1442.84 2473.30 0.583 0.5757
## Week_15 1522.11 1773.50 0.858 0.4157
## Week_16 789.24 767.77 1.028 0.3340
## Week_17 -1225.56 1118.93 -1.095 0.3053
## Week_18 1141.85 857.40 1.332 0.2196
## Week_19 993.73 536.69 1.852 0.1012
## Week_20 1066.51 1196.28 0.892 0.3987
## Week_21 -839.57 1048.31 -0.801 0.4463
## Week_22 -927.81 658.88 -1.408 0.1967
## Week_23 -1178.51 1022.20 -1.153 0.2822
## Week_24 1360.14 1035.58 1.313 0.2255
## Week_25 -2343.97 1288.26 -1.819 0.1063
## Week_26 269.62 355.57 0.758 0.4700
## Week_27 3366.10 1037.66 3.244 0.0118 *
## Week_28 -224.66 1029.78 -0.218 0.8328
## Week_29 1036.99 893.18 1.161 0.2791
## Week_30 463.16 667.04 0.694 0.5071
## Week_31 3845.57 2933.00 1.311 0.2262
## Week_32 -1285.01 869.03 -1.479 0.1775
## Week_33 -673.49 1353.41 -0.498 0.6321
## Week_34 6794.01 2334.77 2.910 0.0196 *
## Week_35 -2673.52 1413.09 -1.892 0.0951 .
## Week_36 4127.59 1543.27 2.675 0.0282 *
## Week_37 -2474.94 2545.44 -0.972 0.3594
## Week_38 -349.25 1499.05 -0.233 0.8216
## Week_39 -695.63 1258.93 -0.553 0.5957
## Week_40 -3333.10 2036.66 -1.637 0.1404
## Week_41 -613.71 1882.25 -0.326 0.7528
## Week_42 3909.47 1567.27 2.494 0.0373 *
## Week_43 -3417.51 1941.57 -1.760 0.1164
## Week_44 315.47 1455.00 0.217 0.8338
## Week_45 -4087.96 2320.44 -1.762 0.1161
## Week_46 4392.16 2178.83 2.016 0.0786 .
## Week_47 -625.61 985.86 -0.635 0.5434
## Week_48 956.91 1276.17 0.750 0.4748
## Week_49 1533.99 1223.71 1.254 0.2454
## Week_50 -1444.04 1282.89 -1.126 0.2930
## Week_51 -1701.51 935.50 -1.819 0.1064
## Week_52 1976.93 1626.46 1.215 0.2588
## Week_53 -1614.43 1029.99 -1.567 0.1557
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8666 on 8 degrees of freedom
## Multiple R-squared: 0.9698, Adjusted R-squared: 0.7694
## F-statistic: 4.841 on 53 and 8 DF, p-value: 0.01152
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5837.8 -1725.3 -198.2 1208.5 7536.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 123407.92 10478.35 11.777 2.47e-06 ***
## Week_1 806.42 749.53 1.076 0.3133
## Week_2 -46.83 517.93 -0.090 0.9302
## Week_3 899.86 678.96 1.325 0.2216
## Week_4 -1270.65 1184.73 -1.073 0.3148
## Week_5 -69.53 674.92 -0.103 0.9205
## Week_6 86.49 962.84 0.090 0.9306
## Week_7 -317.43 1255.33 -0.253 0.8068
## Week_8 -238.38 973.83 -0.245 0.8128
## Week_9 -164.69 901.09 -0.183 0.8595
## Week_10 202.39 923.17 0.219 0.8320
## Week_11 -500.89 1316.45 -0.380 0.7135
## Week_12 -479.77 842.63 -0.569 0.5847
## Week_13 -292.09 965.49 -0.303 0.7700
## Week_14 2049.21 2014.88 1.017 0.3389
## Week_15 1394.37 1444.79 0.965 0.3628
## Week_16 81.82 625.46 0.131 0.8991
## Week_17 44.46 911.54 0.049 0.9623
## Week_18 -78.92 698.49 -0.113 0.9128
## Week_19 394.91 437.22 0.903 0.3928
## Week_20 535.20 974.55 0.549 0.5979
## Week_21 -553.01 854.01 -0.648 0.5354
## Week_22 -300.79 536.76 -0.560 0.5906
## Week_23 -437.69 832.73 -0.526 0.6134
## Week_24 771.14 843.64 0.914 0.3874
## Week_25 -1660.72 1049.49 -1.582 0.1522
## Week_26 -132.08 289.67 -0.456 0.6605
## Week_27 1726.28 845.34 2.042 0.0754 .
## Week_28 67.73 838.92 0.081 0.9376
## Week_29 495.58 727.63 0.681 0.5150
## Week_30 278.22 543.41 0.512 0.6225
## Week_31 3385.97 2389.38 1.417 0.1942
## Week_32 212.87 707.95 0.301 0.7713
## Week_33 -1152.92 1102.56 -1.046 0.3263
## Week_34 1066.17 1902.03 0.561 0.5905
## Week_35 624.93 1151.18 0.543 0.6020
## Week_36 -2375.88 1257.23 -1.890 0.0955 .
## Week_37 -1847.96 2073.65 -0.891 0.3989
## Week_38 649.91 1221.20 0.532 0.6091
## Week_39 88.93 1025.59 0.087 0.9330
## Week_40 -1053.59 1659.17 -0.635 0.5432
## Week_41 804.23 1533.38 0.524 0.6142
## Week_42 1521.51 1276.78 1.192 0.2675
## Week_43 42.96 1581.70 0.027 0.9790
## Week_44 -1031.52 1185.32 -0.870 0.4095
## Week_45 -2714.56 1890.35 -1.436 0.1889
## Week_46 3581.81 1774.99 2.018 0.0783 .
## Week_47 268.70 803.14 0.335 0.7466
## Week_48 1108.38 1039.64 1.066 0.3175
## Week_49 443.45 996.90 0.445 0.6682
## Week_50 -952.43 1045.11 -0.911 0.3888
## Week_51 -326.53 762.11 -0.428 0.6796
## Week_52 324.71 1325.00 0.245 0.8126
## Week_53 -68.02 839.08 -0.081 0.9374
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7060 on 8 degrees of freedom
## Multiple R-squared: 0.9275, Adjusted R-squared: 0.4472
## F-statistic: 1.931 on 53 and 8 DF, p-value: 0.1623
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3765.4 -913.4 -359.8 954.4 4594.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 36184.14 6340.82 5.707 0.000451 ***
## Week_1 421.32 453.57 0.929 0.380112
## Week_2 -406.31 313.42 -1.296 0.230984
## Week_3 549.88 410.86 1.338 0.217566
## Week_4 89.98 716.92 0.126 0.903221
## Week_5 -56.65 408.42 -0.139 0.893107
## Week_6 -1020.79 582.65 -1.752 0.117878
## Week_7 -230.95 759.65 -0.304 0.768870
## Week_8 1753.05 589.30 2.975 0.017740 *
## Week_9 -853.03 545.28 -1.564 0.156359
## Week_10 127.30 558.64 0.228 0.825462
## Week_11 -1291.86 796.63 -1.622 0.143535
## Week_12 -263.73 509.91 -0.517 0.618997
## Week_13 251.56 584.25 0.431 0.678142
## Week_14 1259.70 1219.28 1.033 0.331753
## Week_15 477.74 874.29 0.546 0.599675
## Week_16 -45.16 378.49 -0.119 0.907962
## Week_17 -935.08 551.60 -1.695 0.128482
## Week_18 539.98 422.68 1.278 0.237243
## Week_19 531.49 264.58 2.009 0.079419 .
## Week_20 759.79 589.74 1.288 0.233632
## Week_21 -44.56 516.79 -0.086 0.933410
## Week_22 -95.45 324.81 -0.294 0.776346
## Week_23 -660.23 503.92 -1.310 0.226494
## Week_24 94.10 510.52 0.184 0.858345
## Week_25 -237.42 635.08 -0.374 0.718232
## Week_26 -186.85 175.29 -1.066 0.317553
## Week_27 1762.13 511.54 3.445 0.008762 **
## Week_28 -681.49 507.66 -1.342 0.216306
## Week_29 -174.30 440.32 -0.396 0.702555
## Week_30 302.91 328.84 0.921 0.383902
## Week_31 918.94 1445.90 0.636 0.542818
## Week_32 -66.10 428.41 -0.154 0.881195
## Week_33 -718.92 667.20 -1.078 0.312663
## Week_34 2947.85 1150.99 2.561 0.033587 *
## Week_35 -1253.79 696.62 -1.800 0.109583
## Week_36 1010.79 760.80 1.329 0.220628
## Week_37 -676.69 1254.84 -0.539 0.604384
## Week_38 86.66 738.99 0.117 0.909536
## Week_39 125.72 620.62 0.203 0.844523
## Week_40 -1368.57 1004.02 -1.363 0.209980
## Week_41 722.08 927.90 0.778 0.458852
## Week_42 1921.01 772.63 2.486 0.037737 *
## Week_43 -572.65 957.14 -0.598 0.566194
## Week_44 -751.93 717.28 -1.048 0.325130
## Week_45 -841.69 1143.92 -0.736 0.482867
## Week_46 1151.20 1074.11 1.072 0.315088
## Week_47 -462.00 486.01 -0.951 0.369636
## Week_48 592.93 629.12 0.942 0.373537
## Week_49 263.89 603.26 0.437 0.673364
## Week_50 -398.73 632.43 -0.630 0.545969
## Week_51 -874.17 461.18 -1.896 0.094619 .
## Week_52 585.33 801.80 0.730 0.486204
## Week_53 -435.37 507.76 -0.857 0.416150
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4272 on 8 degrees of freedom
## Multiple R-squared: 0.9421, Adjusted R-squared: 0.5586
## F-statistic: 2.456 on 53 and 8 DF, p-value: 0.08845
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3404.7 -1029.7 -210.9 722.1 4629.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 23961.701 6607.473 3.626 0.00672 **
## Week_1 -702.709 472.641 -1.487 0.17539
## Week_2 157.816 326.599 0.483 0.64189
## Week_3 -292.068 428.139 -0.682 0.51439
## Week_4 1208.512 747.071 1.618 0.14440
## Week_5 -1049.263 425.592 -2.465 0.03899 *
## Week_6 -630.246 607.154 -1.038 0.32961
## Week_7 751.474 791.593 0.949 0.37025
## Week_8 1135.322 614.080 1.849 0.10166
## Week_9 -500.700 568.214 -0.881 0.40392
## Week_10 -701.512 582.137 -1.205 0.26261
## Week_11 -1225.466 830.130 -1.476 0.17812
## Week_12 -449.506 531.350 -0.846 0.42215
## Week_13 933.924 608.820 1.534 0.16358
## Week_14 -633.648 1270.552 -0.499 0.63140
## Week_15 1312.632 911.059 1.441 0.18762
## Week_16 652.696 394.407 1.655 0.13654
## Week_17 -634.967 574.801 -1.105 0.30142
## Week_18 -487.901 440.455 -1.108 0.30017
## Week_19 232.146 275.702 0.842 0.42423
## Week_20 1266.244 614.536 2.060 0.07330 .
## Week_21 -303.061 538.526 -0.563 0.58902
## Week_22 -1094.305 338.472 -3.233 0.01200 *
## Week_23 661.858 525.109 1.260 0.24304
## Week_24 57.603 531.987 0.108 0.91644
## Week_25 -4.102 661.788 -0.006 0.99521
## Week_26 -61.315 182.661 -0.336 0.74575
## Week_27 463.250 533.055 0.869 0.41014
## Week_28 772.263 529.007 1.460 0.18246
## Week_29 -846.214 458.834 -1.844 0.10237
## Week_30 -29.721 342.664 -0.087 0.93301
## Week_31 1311.893 1506.701 0.871 0.40928
## Week_32 -88.776 446.424 -0.199 0.84733
## Week_33 -1191.185 695.254 -1.713 0.12501
## Week_34 1181.500 1199.389 0.985 0.35343
## Week_35 366.011 725.915 0.504 0.62771
## Week_36 -315.120 792.791 -0.397 0.70141
## Week_37 915.710 1307.612 0.700 0.50360
## Week_38 -1073.071 770.070 -1.393 0.20097
## Week_39 -931.650 646.721 -1.441 0.18767
## Week_40 377.127 1046.245 0.360 0.72784
## Week_41 -810.362 966.925 -0.838 0.42631
## Week_42 528.123 805.117 0.656 0.53026
## Week_43 -1214.846 997.397 -1.218 0.25792
## Week_44 1381.988 747.445 1.849 0.10164
## Week_45 -1594.716 1192.025 -1.338 0.21774
## Week_46 1576.992 1119.280 1.409 0.19652
## Week_47 438.031 506.444 0.865 0.41227
## Week_48 -479.170 655.580 -0.731 0.48569
## Week_49 99.753 628.629 0.159 0.87785
## Week_50 -512.787 659.030 -0.778 0.45891
## Week_51 9.542 480.571 0.020 0.98464
## Week_52 -301.734 835.522 -0.361 0.72735
## Week_53 -197.042 529.111 -0.372 0.71927
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4452 on 8 degrees of freedom
## Multiple R-squared: 0.9341, Adjusted R-squared: 0.4972
## F-statistic: 2.138 on 53 and 8 DF, p-value: 0.1266
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10582.2 -2734.3 -964.6 2582.2 12444.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86931.8 19493.7 4.459 0.00211 **
## Week_1 622.7 1394.4 0.447 0.66705
## Week_2 -813.6 963.6 -0.844 0.42301
## Week_3 -1019.3 1263.1 -0.807 0.44301
## Week_4 1161.6 2204.0 0.527 0.61246
## Week_5 974.9 1255.6 0.776 0.45985
## Week_6 -3132.8 1791.3 -1.749 0.11842
## Week_7 2375.3 2335.4 1.017 0.33888
## Week_8 1280.3 1811.7 0.707 0.49982
## Week_9 -1105.3 1676.4 -0.659 0.52820
## Week_10 -830.9 1717.5 -0.484 0.64148
## Week_11 -555.4 2449.1 -0.227 0.82630
## Week_12 -127.8 1567.6 -0.082 0.93701
## Week_13 -593.5 1796.2 -0.330 0.74957
## Week_14 511.5 3748.5 0.136 0.89483
## Week_15 3093.1 2687.9 1.151 0.28306
## Week_16 1995.0 1163.6 1.715 0.12477
## Week_17 -2041.0 1695.8 -1.204 0.26317
## Week_18 845.6 1299.5 0.651 0.53344
## Week_19 1770.3 813.4 2.176 0.06120 .
## Week_20 1772.9 1813.0 0.978 0.35679
## Week_21 948.4 1588.8 0.597 0.56708
## Week_22 -988.1 998.6 -0.989 0.35141
## Week_23 -3053.1 1549.2 -1.971 0.08425 .
## Week_24 1165.0 1569.5 0.742 0.47915
## Week_25 -1809.0 1952.4 -0.927 0.38128
## Week_26 -495.9 538.9 -0.920 0.38437
## Week_27 3532.2 1572.6 2.246 0.05490 .
## Week_28 912.1 1560.7 0.584 0.57503
## Week_29 2202.8 1353.7 1.627 0.14232
## Week_30 447.8 1010.9 0.443 0.66954
## Week_31 -4140.4 4445.2 -0.931 0.37888
## Week_32 103.0 1317.1 0.078 0.93961
## Week_33 -4513.0 2051.2 -2.200 0.05898 .
## Week_34 4737.9 3538.5 1.339 0.21738
## Week_35 -1711.8 2141.6 -0.799 0.44720
## Week_36 4970.6 2338.9 2.125 0.06629 .
## Week_37 -1614.6 3857.8 -0.419 0.68658
## Week_38 178.6 2271.9 0.079 0.93928
## Week_39 -1377.1 1908.0 -0.722 0.49099
## Week_40 -2170.8 3086.7 -0.703 0.50183
## Week_41 841.9 2852.7 0.295 0.77541
## Week_42 4085.1 2375.3 1.720 0.12377
## Week_43 -2221.6 2942.6 -0.755 0.47189
## Week_44 150.5 2205.2 0.068 0.94728
## Week_45 -3618.9 3516.8 -1.029 0.33357
## Week_46 4366.6 3302.2 1.322 0.22261
## Week_47 -1076.3 1494.1 -0.720 0.49184
## Week_48 3038.5 1934.1 1.571 0.15482
## Week_49 538.8 1854.6 0.291 0.77881
## Week_50 -2114.1 1944.3 -1.087 0.30856
## Week_51 -1203.2 1417.8 -0.849 0.42073
## Week_52 1993.5 2465.0 0.809 0.44207
## Week_53 -3387.0 1561.0 -2.170 0.06184 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13130 on 8 degrees of freedom
## Multiple R-squared: 0.9163, Adjusted R-squared: 0.3619
## F-statistic: 1.653 on 53 and 8 DF, p-value: 0.2305
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7425.1 -1830.7 159.5 1640.6 10838.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 38575.24 13283.48 2.904 0.0198 *
## Week_1 -1403.29 950.18 -1.477 0.1780
## Week_2 -75.63 656.59 -0.115 0.9111
## Week_3 -1129.77 860.72 -1.313 0.2257
## Week_4 2132.49 1501.89 1.420 0.1934
## Week_5 -116.15 855.60 -0.136 0.8954
## Week_6 -1094.49 1220.61 -0.897 0.3961
## Week_7 2670.75 1591.40 1.678 0.1318
## Week_8 -1066.28 1234.53 -0.864 0.4129
## Week_9 1750.92 1142.32 1.533 0.1639
## Week_10 -2646.91 1170.31 -2.262 0.0536 .
## Week_11 2260.02 1668.87 1.354 0.2127
## Week_12 -2260.07 1068.21 -2.116 0.0673 .
## Week_13 1660.71 1223.96 1.357 0.2119
## Week_14 -3561.38 2554.28 -1.394 0.2007
## Week_15 2932.58 1831.57 1.601 0.1480
## Week_16 -81.53 792.91 -0.103 0.9206
## Week_17 1751.79 1155.56 1.516 0.1680
## Week_18 -435.27 885.48 -0.492 0.6362
## Week_19 358.92 554.26 0.648 0.5354
## Week_20 957.48 1235.45 0.775 0.4606
## Week_21 479.84 1082.64 0.443 0.6693
## Week_22 191.51 680.45 0.281 0.7855
## Week_23 270.30 1055.66 0.256 0.8044
## Week_24 957.57 1069.49 0.895 0.3967
## Week_25 -827.69 1330.44 -0.622 0.5512
## Week_26 87.36 367.22 0.238 0.8179
## Week_27 -1019.80 1071.64 -0.952 0.3692
## Week_28 1946.71 1063.50 1.830 0.1046
## Week_29 -162.84 922.43 -0.177 0.8643
## Week_30 244.00 688.88 0.354 0.7323
## Week_31 -5340.99 3029.03 -1.763 0.1159
## Week_32 -1520.77 897.48 -1.694 0.1286
## Week_33 -1147.44 1397.72 -0.821 0.4355
## Week_34 3479.24 2411.22 1.443 0.1870
## Week_35 -3175.18 1459.36 -2.176 0.0613 .
## Week_36 3175.92 1593.80 1.993 0.0814 .
## Week_37 2750.35 2628.79 1.046 0.3260
## Week_38 -2153.98 1548.13 -1.391 0.2016
## Week_39 -373.91 1300.15 -0.288 0.7810
## Week_40 1410.62 2103.34 0.671 0.5213
## Week_41 -1818.99 1943.88 -0.936 0.3768
## Week_42 -1358.87 1618.59 -0.840 0.4255
## Week_43 339.94 2005.14 0.170 0.8696
## Week_44 2361.83 1502.64 1.572 0.1546
## Week_45 -844.36 2396.41 -0.352 0.7337
## Week_46 1400.81 2250.17 0.623 0.5509
## Week_47 -434.00 1018.14 -0.426 0.6812
## Week_48 -826.90 1317.96 -0.627 0.5479
## Week_49 179.49 1263.78 0.142 0.8906
## Week_50 -818.68 1324.90 -0.618 0.5538
## Week_51 523.05 966.13 0.541 0.6030
## Week_52 -1834.04 1679.71 -1.092 0.3067
## Week_53 -330.80 1063.71 -0.311 0.7638
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8950 on 8 degrees of freedom
## Multiple R-squared: 0.885, Adjusted R-squared: 0.1231
## F-statistic: 1.162 on 53 and 8 DF, p-value: 0.4452
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9574.4 -2626.2 -828.6 2319.2 12062.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 96214.07 18287.79 5.261 0.000763 ***
## Week_1 864.57 1308.15 0.661 0.527240
## Week_2 -647.67 903.94 -0.716 0.494067
## Week_3 1316.81 1184.98 1.111 0.298740
## Week_4 -216.05 2067.70 -0.104 0.919354
## Week_5 -50.65 1177.93 -0.043 0.966754
## Week_6 -2597.43 1680.45 -1.546 0.160764
## Week_7 1128.01 2190.93 0.515 0.620575
## Week_8 1744.02 1699.62 1.026 0.334855
## Week_9 -1174.94 1572.67 -0.747 0.476387
## Week_10 19.93 1611.20 0.012 0.990432
## Week_11 -3106.88 2297.59 -1.352 0.213281
## Week_12 -749.85 1470.64 -0.510 0.623899
## Week_13 966.28 1685.06 0.573 0.582104
## Week_14 1617.57 3516.56 0.460 0.657769
## Week_15 2003.33 2521.58 0.794 0.449843
## Week_16 1978.71 1091.62 1.813 0.107456
## Week_17 -2610.72 1590.90 -1.641 0.139419
## Week_18 1201.27 1219.06 0.985 0.353288
## Week_19 2049.35 763.07 2.686 0.027682 *
## Week_20 1696.67 1700.88 0.998 0.347722
## Week_21 -414.95 1490.50 -0.278 0.787770
## Week_22 -642.76 936.80 -0.686 0.512030
## Week_23 -2279.89 1453.37 -1.569 0.155357
## Week_24 964.27 1472.40 0.655 0.530909
## Week_25 -2834.51 1831.66 -1.548 0.160329
## Week_26 -253.21 505.56 -0.501 0.629964
## Week_27 4813.40 1475.36 3.263 0.011484 *
## Week_28 465.76 1464.15 0.318 0.758547
## Week_29 947.86 1269.94 0.746 0.476794
## Week_30 276.49 948.41 0.292 0.778061
## Week_31 4293.72 4170.16 1.030 0.333305
## Week_32 -20.41 1235.59 -0.017 0.987228
## Week_33 -3697.88 1924.28 -1.922 0.090878 .
## Week_34 7274.26 3319.60 2.191 0.059799 .
## Week_35 -690.19 2009.15 -0.344 0.740057
## Week_36 2965.91 2194.24 1.352 0.213451
## Week_37 -5179.06 3619.13 -1.431 0.190304
## Week_38 186.13 2131.36 0.087 0.932556
## Week_39 -1639.98 1789.96 -0.916 0.386342
## Week_40 -2550.36 2895.74 -0.881 0.404146
## Week_41 2136.35 2676.20 0.798 0.447757
## Week_42 5077.45 2228.36 2.279 0.052188 .
## Week_43 -2317.80 2760.54 -0.840 0.425501
## Week_44 -549.43 2068.73 -0.266 0.797272
## Week_45 -7212.95 3299.22 -2.186 0.060271 .
## Week_46 7210.22 3097.88 2.327 0.048352 *
## Week_47 -70.61 1401.71 -0.050 0.961059
## Week_48 3032.03 1814.48 1.671 0.133262
## Week_49 1772.54 1739.88 1.019 0.338130
## Week_50 -3077.15 1824.03 -1.687 0.130084
## Week_51 -1938.64 1330.10 -1.458 0.183080
## Week_52 2267.84 2312.51 0.981 0.355471
## Week_53 -2077.35 1464.44 -1.419 0.193798
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12320 on 8 degrees of freedom
## Multiple R-squared: 0.9484, Adjusted R-squared: 0.6068
## F-statistic: 2.776 on 53 and 8 DF, p-value: 0.06325
Kelowna weekly
## [1] "NA value found at row 17 and column 47"
## [1] "NA value found at row 17 and column 48"
## [1] "NA value found at row 17 and column 49"
## [1] "NA value found at row 57 and column 55"
## [1] "There are 4 NA in the matrix X in Kelowna station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -30154.8 -6135.8 712.3 7224.2 26419.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 254454.9 70907.1 3.589 0.01152 *
## Week_1 9439.3 3995.8 2.362 0.05611 .
## Week_2 -3840.2 2552.3 -1.505 0.18313
## Week_3 -4066.3 4223.3 -0.963 0.37281
## Week_4 6566.7 3577.6 1.836 0.11610
## Week_5 -6977.7 3332.6 -2.094 0.08117 .
## Week_6 2346.9 2280.3 1.029 0.34306
## Week_7 -4405.8 2991.0 -1.473 0.19118
## Week_8 6088.8 3069.5 1.984 0.09455 .
## Week_9 -2005.2 4852.3 -0.413 0.69379
## Week_10 -197.9 3949.4 -0.050 0.96166
## Week_11 -5271.4 3296.5 -1.599 0.16092
## Week_12 -314.6 3867.2 -0.081 0.93780
## Week_13 2065.0 5988.0 0.345 0.74197
## Week_14 6474.1 5175.1 1.251 0.25749
## Week_15 15634.6 4786.3 3.267 0.01711 *
## Week_16 -1074.1 4244.7 -0.253 0.80867
## Week_17 -24290.2 4655.2 -5.218 0.00198 **
## Week_18 2128.1 3328.9 0.639 0.54626
## Week_19 5076.9 3173.8 1.600 0.16080
## Week_20 1830.8 2936.3 0.624 0.55590
## Week_21 5182.3 3423.1 1.514 0.18082
## Week_22 -12541.4 3919.7 -3.200 0.01861 *
## Week_23 -1653.5 3275.6 -0.505 0.63171
## Week_24 9563.5 3834.2 2.494 0.04689 *
## Week_25 -8258.8 3408.0 -2.423 0.05162 .
## Week_26 2224.8 1214.6 1.832 0.11670
## Week_27 1278.9 5758.2 0.222 0.83160
## Week_28 5099.3 6685.0 0.763 0.47449
## Week_29 -308.1 8341.8 -0.037 0.97174
## Week_30 -1188.9 6547.5 -0.182 0.86189
## Week_31 1457.7 5650.9 0.258 0.80506
## Week_32 -2317.8 9721.5 -0.238 0.81949
## Week_33 17332.7 7236.2 2.395 0.05364 .
## Week_34 6067.5 11218.0 0.541 0.60807
## Week_35 7128.2 6922.9 1.030 0.34288
## Week_36 -34922.4 6136.6 -5.691 0.00127 **
## Week_37 9970.6 5411.6 1.842 0.11499
## Week_38 1583.9 5484.0 0.289 0.78244
## Week_39 1229.5 5659.8 0.217 0.83523
## Week_40 3828.9 6468.2 0.592 0.57549
## Week_41 -13650.5 6388.0 -2.137 0.07648 .
## Week_42 3479.1 7900.1 0.440 0.67508
## Week_43 5254.8 8613.5 0.610 0.56419
## Week_44 2164.5 3729.6 0.580 0.58279
## Week_45 2399.5 6028.6 0.398 0.70439
## Week_46 -4232.3 4628.8 -0.914 0.39580
## Week_47 5739.4 4220.4 1.360 0.22273
## Week_48 2652.9 3446.3 0.770 0.47065
## Week_49 -5711.5 3232.3 -1.767 0.12765
## Week_50 2010.6 5630.5 0.357 0.73325
## Week_51 4146.0 3824.5 1.084 0.31996
## Week_52 1642.3 3186.3 0.515 0.62468
## Week_53 -1057.9 2569.2 -0.412 0.69481
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 35570 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9606, Adjusted R-squared: 0.6121
## F-statistic: 2.757 on 53 and 6 DF, p-value: 0.1008
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4248 -1103 18 1152 3842
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 33590.31 10323.46 3.254 0.01738 *
## Week_1 1054.09 581.76 1.812 0.11996
## Week_2 -664.55 371.59 -1.788 0.12393
## Week_3 -277.34 614.87 -0.451 0.66779
## Week_4 586.74 520.87 1.126 0.30300
## Week_5 -715.63 485.20 -1.475 0.19068
## Week_6 369.49 331.98 1.113 0.30831
## Week_7 -702.58 435.47 -1.613 0.15779
## Week_8 913.15 446.89 2.043 0.08704 .
## Week_9 -553.82 706.46 -0.784 0.46289
## Week_10 198.69 575.00 0.346 0.74148
## Week_11 -675.12 479.94 -1.407 0.20915
## Week_12 594.93 563.03 1.057 0.33134
## Week_13 -550.34 871.79 -0.631 0.55114
## Week_14 1322.64 753.44 1.755 0.12971
## Week_15 1404.07 696.85 2.015 0.09054 .
## Week_16 -50.45 617.99 -0.082 0.93759
## Week_17 -2469.89 677.76 -3.644 0.01078 *
## Week_18 138.19 484.65 0.285 0.78513
## Week_19 588.05 462.08 1.273 0.25024
## Week_20 143.15 427.50 0.335 0.74913
## Week_21 553.64 498.37 1.111 0.30914
## Week_22 -1078.15 570.67 -1.889 0.10776
## Week_23 94.57 476.90 0.198 0.84936
## Week_24 422.13 558.22 0.756 0.47816
## Week_25 -389.16 496.17 -0.784 0.46268
## Week_26 160.19 176.83 0.906 0.39991
## Week_27 140.03 838.34 0.167 0.87283
## Week_28 -198.91 973.28 -0.204 0.84482
## Week_29 408.55 1214.49 0.336 0.74802
## Week_30 -318.03 953.26 -0.334 0.75001
## Week_31 -392.14 822.73 -0.477 0.65049
## Week_32 724.27 1415.37 0.512 0.62713
## Week_33 1425.23 1053.53 1.353 0.22487
## Week_34 768.77 1633.24 0.471 0.65448
## Week_35 474.34 1007.91 0.471 0.65453
## Week_36 -3318.04 893.44 -3.714 0.00992 **
## Week_37 940.77 787.88 1.194 0.27752
## Week_38 593.36 798.42 0.743 0.48546
## Week_39 798.80 824.02 0.969 0.36979
## Week_40 762.89 941.72 0.810 0.44881
## Week_41 -1889.89 930.04 -2.032 0.08841 .
## Week_42 -65.53 1150.18 -0.057 0.95641
## Week_43 47.78 1254.05 0.038 0.97084
## Week_44 461.84 543.00 0.851 0.42766
## Week_45 -261.94 877.71 -0.298 0.77543
## Week_46 -375.77 673.92 -0.558 0.59730
## Week_47 219.60 614.45 0.357 0.73304
## Week_48 -28.28 501.76 -0.056 0.95689
## Week_49 -530.60 470.60 -1.128 0.30259
## Week_50 464.74 819.75 0.567 0.59133
## Week_51 348.08 556.81 0.625 0.55490
## Week_52 324.56 463.90 0.700 0.51036
## Week_53 -280.66 374.06 -0.750 0.48145
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5178 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9289, Adjusted R-squared: 0.3007
## F-statistic: 1.479 on 53 and 6 DF, p-value: 0.3307
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14723.5 -3382.8 229.2 4196.2 13326.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 105692.57 31850.27 3.318 0.0160 *
## Week_1 2125.89 1794.85 1.184 0.2810
## Week_2 -1713.57 1146.45 -1.495 0.1856
## Week_3 527.42 1897.01 0.278 0.7903
## Week_4 885.51 1607.00 0.551 0.6015
## Week_5 -1191.23 1496.94 -0.796 0.4565
## Week_6 388.69 1024.25 0.379 0.7174
## Week_7 -858.96 1343.53 -0.639 0.5462
## Week_8 1620.62 1378.77 1.175 0.2844
## Week_9 -1896.36 2179.59 -0.870 0.4177
## Week_10 1186.41 1774.00 0.669 0.5285
## Week_11 -1862.62 1480.74 -1.258 0.2552
## Week_12 1480.00 1737.07 0.852 0.4269
## Week_13 -2149.96 2689.69 -0.799 0.4546
## Week_14 3958.42 2324.55 1.703 0.1395
## Week_15 1740.71 2149.94 0.810 0.4490
## Week_16 1125.31 1906.64 0.590 0.5766
## Week_17 -4571.97 2091.04 -2.186 0.0714 .
## Week_18 -526.76 1495.27 -0.352 0.7367
## Week_19 1760.62 1425.62 1.235 0.2630
## Week_20 814.17 1318.93 0.617 0.5597
## Week_21 1208.20 1537.60 0.786 0.4619
## Week_22 -3277.87 1760.65 -1.862 0.1120
## Week_23 387.68 1471.34 0.263 0.8010
## Week_24 1790.94 1722.25 1.040 0.3385
## Week_25 -2411.54 1530.79 -1.575 0.1662
## Week_26 1273.79 545.56 2.335 0.0583 .
## Week_27 -817.11 2586.47 -0.316 0.7628
## Week_28 58.59 3002.79 0.020 0.9851
## Week_29 2220.45 3746.98 0.593 0.5751
## Week_30 -1671.65 2941.03 -0.568 0.5904
## Week_31 658.52 2538.31 0.259 0.8040
## Week_32 1744.70 4366.73 0.400 0.7033
## Week_33 2876.75 3250.40 0.885 0.4102
## Week_34 4771.24 5038.91 0.947 0.3803
## Week_35 1581.16 3109.63 0.508 0.6293
## Week_36 -7086.68 2756.46 -2.571 0.0423 *
## Week_37 1988.60 2430.80 0.818 0.4446
## Week_38 -107.79 2463.32 -0.044 0.9665
## Week_39 981.25 2542.31 0.386 0.7128
## Week_40 853.83 2905.41 0.294 0.7788
## Week_41 -3789.38 2869.38 -1.321 0.2348
## Week_42 331.13 3548.57 0.093 0.9287
## Week_43 -598.94 3869.04 -0.155 0.8821
## Week_44 1464.76 1675.28 0.874 0.4156
## Week_45 -1264.21 2707.93 -0.467 0.6571
## Week_46 -960.49 2079.20 -0.462 0.6604
## Week_47 -120.36 1895.73 -0.063 0.9514
## Week_48 82.81 1548.04 0.053 0.9591
## Week_49 -633.68 1451.90 -0.436 0.6778
## Week_50 2907.58 2529.13 1.150 0.2940
## Week_51 -510.12 1717.89 -0.297 0.7765
## Week_52 1543.22 1431.23 1.078 0.3224
## Week_53 -770.75 1154.06 -0.668 0.5291
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15980 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9185, Adjusted R-squared: 0.1982
## F-statistic: 1.275 on 53 and 6 DF, p-value: 0.4139
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6787 -2096 146 1982 12627
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 120001.02 20945.20 5.729 0.00123 **
## Week_1 1001.52 1180.32 0.849 0.42870
## Week_2 85.80 753.92 0.114 0.91310
## Week_3 -1457.72 1247.50 -1.169 0.28692
## Week_4 1821.07 1056.79 1.723 0.13562
## Week_5 -1664.96 984.41 -1.691 0.14173
## Week_6 84.04 673.56 0.125 0.90479
## Week_7 -421.76 883.52 -0.477 0.65000
## Week_8 973.76 906.70 1.074 0.32412
## Week_9 -161.96 1433.33 -0.113 0.91372
## Week_10 -288.02 1166.61 -0.247 0.81323
## Week_11 -638.92 973.76 -0.656 0.53607
## Week_12 8.31 1142.32 0.007 0.99443
## Week_13 527.75 1768.78 0.298 0.77548
## Week_14 530.75 1528.66 0.347 0.74029
## Week_15 2076.98 1413.83 1.469 0.19221
## Week_16 -548.24 1253.83 -0.437 0.67723
## Week_17 -3229.28 1375.10 -2.348 0.05718 .
## Week_18 441.39 983.31 0.449 0.66928
## Week_19 -197.83 937.51 -0.211 0.83986
## Week_20 307.69 867.35 0.355 0.73491
## Week_21 888.25 1011.15 0.878 0.41348
## Week_22 -1571.37 1157.83 -1.357 0.22356
## Week_23 -713.96 967.58 -0.738 0.48843
## Week_24 466.58 1132.57 0.412 0.69468
## Week_25 494.08 1006.67 0.491 0.64099
## Week_26 -399.71 358.77 -1.114 0.30786
## Week_27 1399.70 1700.90 0.823 0.44202
## Week_28 536.30 1974.68 0.272 0.79504
## Week_29 717.21 2464.07 0.291 0.78080
## Week_30 448.10 1934.06 0.232 0.82448
## Week_31 -1275.62 1669.23 -0.764 0.47372
## Week_32 2028.87 2871.63 0.707 0.50636
## Week_33 1298.57 2137.51 0.608 0.56578
## Week_34 -2967.45 3313.66 -0.896 0.40500
## Week_35 2001.87 2044.94 0.979 0.36542
## Week_36 -5875.36 1812.69 -3.241 0.01766 *
## Week_37 2532.70 1598.53 1.584 0.16420
## Week_38 -139.24 1619.92 -0.086 0.93430
## Week_39 903.11 1671.86 0.540 0.60852
## Week_40 822.39 1910.64 0.430 0.68192
## Week_41 -892.41 1886.95 -0.473 0.65297
## Week_42 675.40 2333.59 0.289 0.78200
## Week_43 2540.30 2544.34 0.998 0.35663
## Week_44 -522.64 1101.69 -0.474 0.65198
## Week_45 366.61 1780.77 0.206 0.84370
## Week_46 681.99 1367.31 0.499 0.63569
## Week_47 527.08 1246.66 0.423 0.68718
## Week_48 1045.80 1018.01 1.027 0.34390
## Week_49 -1266.77 954.79 -1.327 0.23285
## Week_50 241.37 1663.19 0.145 0.88937
## Week_51 830.84 1129.71 0.735 0.48981
## Week_52 -582.00 941.20 -0.618 0.55906
## Week_53 473.67 758.93 0.624 0.55551
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10510 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.8785, Adjusted R-squared: -0.1946
## F-statistic: 0.8187 on 53 and 6 DF, p-value: 0.6899
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4257.5 -909.1 62.1 1143.0 4236.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 29967.882 10530.540 2.846 0.0293 *
## Week_1 810.150 593.426 1.365 0.2212
## Week_2 -652.709 379.046 -1.722 0.1359
## Week_3 131.664 627.203 0.210 0.8407
## Week_4 193.406 531.316 0.364 0.7283
## Week_5 -450.415 494.929 -0.910 0.3979
## Week_6 256.779 338.644 0.758 0.4770
## Week_7 -664.789 444.206 -1.497 0.1851
## Week_8 830.048 455.858 1.821 0.1185
## Week_9 -403.779 720.629 -0.560 0.5956
## Week_10 159.243 586.531 0.271 0.7951
## Week_11 -714.886 489.572 -1.460 0.1945
## Week_12 505.785 574.321 0.881 0.4124
## Week_13 -373.711 889.282 -0.420 0.6889
## Week_14 1195.488 768.557 1.555 0.1708
## Week_15 390.651 710.826 0.550 0.6025
## Week_16 696.135 630.385 1.104 0.3118
## Week_17 -2186.647 691.354 -3.163 0.0195 *
## Week_18 138.100 494.376 0.279 0.7894
## Week_19 704.842 471.349 1.495 0.1854
## Week_20 169.868 436.073 0.390 0.7103
## Week_21 525.853 508.371 1.034 0.3408
## Week_22 -838.146 582.118 -1.440 0.2000
## Week_23 -210.753 486.465 -0.433 0.6800
## Week_24 533.804 569.420 0.937 0.3847
## Week_25 -462.799 506.121 -0.914 0.3958
## Week_26 288.195 180.377 1.598 0.1612
## Week_27 -413.028 855.157 -0.483 0.6462
## Week_28 129.790 992.801 0.131 0.9003
## Week_29 55.489 1238.850 0.045 0.9657
## Week_30 -425.918 972.382 -0.438 0.6767
## Week_31 86.052 839.231 0.103 0.9217
## Week_32 1269.551 1443.757 0.879 0.4130
## Week_33 773.410 1074.667 0.720 0.4988
## Week_34 1592.584 1665.997 0.956 0.3760
## Week_35 -2.384 1028.127 -0.002 0.9982
## Week_36 -2857.637 911.358 -3.136 0.0202 *
## Week_37 684.519 803.686 0.852 0.4270
## Week_38 563.159 814.440 0.691 0.5151
## Week_39 480.921 840.554 0.572 0.5880
## Week_40 469.918 960.605 0.489 0.6421
## Week_41 -1648.595 948.694 -1.738 0.1329
## Week_42 1095.947 1173.252 0.934 0.3863
## Week_43 -744.176 1279.207 -0.582 0.5819
## Week_44 450.345 553.891 0.813 0.4472
## Week_45 -261.521 895.313 -0.292 0.7800
## Week_46 30.213 687.438 0.044 0.9664
## Week_47 164.912 626.777 0.263 0.8013
## Week_48 -232.763 511.822 -0.455 0.6653
## Week_49 -519.140 480.037 -1.081 0.3210
## Week_50 525.198 836.196 0.628 0.5531
## Week_51 333.531 567.981 0.587 0.5785
## Week_52 197.264 473.202 0.417 0.6913
## Week_53 -308.792 381.563 -0.809 0.4492
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5282 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9297, Adjusted R-squared: 0.3085
## F-statistic: 1.497 on 53 and 6 DF, p-value: 0.3244
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3528.5 -943.8 -85.9 1063.8 3455.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60077.04 9333.07 6.437 0.000665 ***
## Week_1 15.02 525.94 0.029 0.978149
## Week_2 -354.00 335.94 -1.054 0.332572
## Week_3 717.52 555.88 1.291 0.244281
## Week_4 -340.72 470.90 -0.724 0.496568
## Week_5 217.01 438.65 0.495 0.638393
## Week_6 -365.02 300.14 -1.216 0.269581
## Week_7 165.25 393.69 0.420 0.689288
## Week_8 29.36 404.02 0.073 0.944433
## Week_9 -166.57 638.68 -0.261 0.802968
## Week_10 -234.08 519.83 -0.450 0.668306
## Week_11 169.53 433.90 0.391 0.709506
## Week_12 262.84 509.01 0.516 0.624073
## Week_13 -1076.35 788.16 -1.366 0.221027
## Week_14 1078.02 681.16 1.583 0.164596
## Week_15 -1559.96 630.00 -2.476 0.048056 *
## Week_16 1827.43 558.70 3.271 0.017016 *
## Week_17 386.71 612.74 0.631 0.551235
## Week_18 -492.61 438.16 -1.124 0.303853
## Week_19 11.51 417.75 0.028 0.978914
## Week_20 989.29 386.49 2.560 0.042925 *
## Week_21 -57.21 450.56 -0.127 0.903112
## Week_22 436.35 515.92 0.846 0.430113
## Week_23 317.56 431.15 0.737 0.489182
## Week_24 -733.99 504.67 -1.454 0.196068
## Week_25 -240.76 448.57 -0.537 0.610760
## Week_26 209.51 159.87 1.311 0.237947
## Week_27 -14.21 757.91 -0.019 0.985648
## Week_28 -131.89 879.91 -0.150 0.885762
## Week_29 206.71 1097.98 0.188 0.856876
## Week_30 -974.75 861.81 -1.131 0.301207
## Week_31 1077.29 743.80 1.448 0.197681
## Week_32 947.29 1279.58 0.740 0.487056
## Week_33 -1773.74 952.46 -1.862 0.111871
## Week_34 3870.94 1476.55 2.622 0.039501 *
## Week_35 675.84 911.21 0.742 0.486281
## Week_36 -1057.40 807.72 -1.309 0.238394
## Week_37 317.53 712.30 0.446 0.671388
## Week_38 841.74 721.83 1.166 0.287815
## Week_39 -1685.51 744.97 -2.263 0.064326 .
## Week_40 103.02 851.37 0.121 0.907638
## Week_41 1151.08 840.81 1.369 0.220034
## Week_42 1809.87 1039.84 1.741 0.132413
## Week_43 -637.56 1133.74 -0.562 0.594247
## Week_44 724.07 490.91 1.475 0.190668
## Week_45 -1348.15 793.50 -1.699 0.140237
## Week_46 794.57 609.27 1.304 0.239978
## Week_47 -391.25 555.50 -0.704 0.507634
## Week_48 -284.07 453.62 -0.626 0.554229
## Week_49 380.32 425.45 0.894 0.405789
## Week_50 385.14 741.11 0.520 0.621892
## Week_51 -95.59 503.39 -0.190 0.855654
## Week_52 44.52 419.39 0.106 0.918929
## Week_53 -356.12 338.17 -1.053 0.332864
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4681 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9412, Adjusted R-squared: 0.4215
## F-statistic: 1.811 on 53 and 6 DF, p-value: 0.2339
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9439.1 -2055.9 -257.6 2199.7 7010.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 68156.459 21733.187 3.136 0.02017 *
## Week_1 2188.683 1224.726 1.787 0.12415
## Week_2 -1597.258 782.284 -2.042 0.08723 .
## Week_3 -942.923 1294.437 -0.728 0.49378
## Week_4 1141.234 1096.544 1.041 0.33810
## Week_5 -377.968 1021.447 -0.370 0.72407
## Week_6 848.260 698.902 1.214 0.27046
## Week_7 -2028.193 916.763 -2.212 0.06892 .
## Week_8 2191.678 940.812 2.330 0.05868 .
## Week_9 -1646.316 1487.251 -1.107 0.31071
## Week_10 -883.528 1210.498 -0.730 0.49296
## Week_11 227.101 1010.390 0.225 0.82962
## Week_12 1723.757 1185.298 1.454 0.19610
## Week_13 -2866.898 1835.322 -1.562 0.16930
## Week_14 2192.277 1586.166 1.382 0.21619
## Week_15 2605.230 1467.021 1.776 0.12610
## Week_16 236.891 1301.004 0.182 0.86151
## Week_17 -5458.131 1426.834 -3.825 0.00871 **
## Week_18 2930.105 1020.306 2.872 0.02836 *
## Week_19 379.006 972.781 0.390 0.71028
## Week_20 667.900 899.978 0.742 0.48603
## Week_21 319.439 1049.189 0.304 0.77106
## Week_22 -706.750 1201.390 -0.588 0.57780
## Week_23 576.682 1003.979 0.574 0.58657
## Week_24 -234.974 1175.183 -0.200 0.84813
## Week_25 -1749.385 1044.545 -1.675 0.14500
## Week_26 691.304 372.267 1.857 0.11269
## Week_27 -572.160 1764.893 -0.324 0.75680
## Week_28 -84.217 2048.967 -0.041 0.96855
## Week_29 1838.951 2556.769 0.719 0.49903
## Week_30 -1449.662 2006.826 -0.722 0.49725
## Week_31 -1477.208 1732.026 -0.853 0.42646
## Week_32 -1827.702 2979.662 -0.613 0.56213
## Week_33 3005.513 2217.924 1.355 0.22418
## Week_34 5139.220 3438.326 1.495 0.18562
## Week_35 1735.325 2121.874 0.818 0.44471
## Week_36 -4388.823 1880.883 -2.333 0.05837 .
## Week_37 2658.598 1658.667 1.603 0.16009
## Week_38 311.665 1680.862 0.185 0.85901
## Week_39 2190.043 1734.756 1.262 0.25363
## Week_40 -1424.282 1982.521 -0.718 0.49951
## Week_41 -3150.295 1957.938 -1.609 0.15874
## Week_42 -997.026 2421.387 -0.412 0.69482
## Week_43 -503.172 2640.060 -0.191 0.85513
## Week_44 810.417 1143.133 0.709 0.50496
## Week_45 -539.623 1847.769 -0.292 0.78009
## Week_46 -1509.091 1418.752 -1.064 0.32840
## Week_47 -667.043 1293.557 -0.516 0.62453
## Week_48 913.235 1056.311 0.865 0.42050
## Week_49 7.926 990.713 0.008 0.99388
## Week_50 979.602 1725.762 0.568 0.59087
## Week_51 -57.064 1172.212 -0.049 0.96275
## Week_52 2582.939 976.605 2.645 0.03829 *
## Week_53 -2250.581 787.479 -2.858 0.02888 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10900 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9517, Adjusted R-squared: 0.5249
## F-statistic: 2.23 on 53 and 6 DF, p-value: 0.1572
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5109.1 -1735.2 102.4 1843.0 6184.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 46765.75 15381.26 3.040 0.02279 *
## Week_1 934.18 866.78 1.078 0.32255
## Week_2 -124.30 553.65 -0.225 0.82981
## Week_3 -828.83 916.11 -0.905 0.40048
## Week_4 542.37 776.06 0.699 0.51079
## Week_5 -959.23 722.91 -1.327 0.23280
## Week_6 1208.17 494.63 2.443 0.05030 .
## Week_7 -566.20 648.82 -0.873 0.41640
## Week_8 -356.02 665.84 -0.535 0.61208
## Week_9 746.36 1052.57 0.709 0.50488
## Week_10 -184.80 856.71 -0.216 0.83636
## Week_11 -186.98 715.08 -0.261 0.80247
## Week_12 304.49 838.87 0.363 0.72907
## Week_13 -1704.26 1298.91 -1.312 0.23746
## Week_14 615.22 1122.58 0.548 0.60344
## Week_15 3881.69 1038.26 3.739 0.00964 **
## Week_16 -2124.09 920.76 -2.307 0.06053 .
## Week_17 -2163.89 1009.82 -2.143 0.07585 .
## Week_18 644.20 722.10 0.892 0.40668
## Week_19 572.37 688.47 0.831 0.43759
## Week_20 -1126.34 636.94 -1.768 0.12741
## Week_21 184.23 742.54 0.248 0.81233
## Week_22 -301.90 850.26 -0.355 0.73469
## Week_23 2346.29 710.55 3.302 0.01637 *
## Week_24 296.40 831.71 0.356 0.73376
## Week_25 -1459.61 739.26 -1.974 0.09576 .
## Week_26 130.54 263.46 0.495 0.63790
## Week_27 178.04 1249.07 0.143 0.89132
## Week_28 1385.44 1450.12 0.955 0.37627
## Week_29 -1226.06 1809.51 -0.678 0.52330
## Week_30 1847.09 1420.29 1.301 0.24114
## Week_31 -855.39 1225.81 -0.698 0.51141
## Week_32 -4285.81 2108.80 -2.032 0.08838 .
## Week_33 3378.40 1569.69 2.152 0.07487 .
## Week_34 1709.14 2433.41 0.702 0.50877
## Week_35 -2221.66 1501.72 -1.479 0.18952
## Week_36 -1743.00 1331.16 -1.309 0.23831
## Week_37 934.09 1173.89 0.796 0.45651
## Week_38 1060.48 1189.60 0.891 0.40701
## Week_39 1056.07 1227.74 0.860 0.42273
## Week_40 -238.15 1403.09 -0.170 0.87080
## Week_41 198.43 1385.69 0.143 0.89082
## Week_42 -2870.61 1713.69 -1.675 0.14493
## Week_43 4173.14 1868.45 2.233 0.06695 .
## Week_44 -820.15 809.03 -1.014 0.34983
## Week_45 -446.36 1307.72 -0.341 0.74449
## Week_46 -848.81 1004.10 -0.845 0.43033
## Week_47 1047.42 915.49 1.144 0.29616
## Week_48 -243.87 747.58 -0.326 0.75534
## Week_49 69.04 701.16 0.098 0.92477
## Week_50 -1356.34 1221.38 -1.111 0.30929
## Week_51 449.93 829.61 0.542 0.60712
## Week_52 1045.16 691.17 1.512 0.18125
## Week_53 -1220.27 557.32 -2.190 0.07112 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7715 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.9336, Adjusted R-squared: 0.3473
## F-statistic: 1.592 on 53 and 6 DF, p-value: 0.2929
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10104.8 -2583.3 -389.8 3367.5 7371.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 96670.63 25554.74 3.783 0.00915 **
## Week_1 3451.33 1440.08 2.397 0.05354 .
## Week_2 -1520.17 919.84 -1.653 0.14949
## Week_3 -1670.56 1522.05 -1.098 0.31447
## Week_4 2831.99 1289.36 2.196 0.07045 .
## Week_5 -2441.82 1201.06 -2.033 0.08829 .
## Week_6 70.14 821.80 0.085 0.93476
## Week_7 -398.52 1077.97 -0.370 0.72430
## Week_8 1010.82 1106.24 0.914 0.39609
## Week_9 -764.43 1748.77 -0.437 0.67731
## Week_10 -188.55 1423.35 -0.132 0.89894
## Week_11 -1134.97 1188.06 -0.955 0.37631
## Week_12 1074.31 1393.72 0.771 0.47007
## Week_13 -1405.91 2158.04 -0.651 0.53888
## Week_14 2414.63 1865.08 1.295 0.24303
## Week_15 3325.83 1724.98 1.928 0.10212
## Week_16 1678.40 1529.77 1.097 0.31464
## Week_17 -7583.73 1677.73 -4.520 0.00402 **
## Week_18 1082.16 1199.72 0.902 0.40181
## Week_19 1245.47 1143.83 1.089 0.31801
## Week_20 1453.33 1058.23 1.373 0.21875
## Week_21 753.84 1233.68 0.611 0.56358
## Week_22 -2476.33 1412.64 -1.753 0.13015
## Week_23 189.76 1180.52 0.161 0.87757
## Week_24 1236.00 1381.83 0.894 0.40552
## Week_25 -2461.33 1228.22 -2.004 0.09192 .
## Week_26 919.70 437.73 2.101 0.08036 .
## Week_27 1493.06 2075.23 0.719 0.49890
## Week_28 533.91 2409.26 0.222 0.83197
## Week_29 2307.32 3006.35 0.767 0.47191
## Week_30 -2755.85 2359.70 -1.168 0.28716
## Week_31 149.63 2036.58 0.073 0.94382
## Week_32 439.09 3503.60 0.125 0.90436
## Week_33 3293.80 2607.92 1.263 0.25345
## Week_34 4976.79 4042.92 1.231 0.26439
## Week_35 4389.25 2494.98 1.759 0.12903
## Week_36 -10722.99 2211.62 -4.848 0.00286 **
## Week_37 3373.03 1950.33 1.729 0.13445
## Week_38 1223.21 1976.42 0.619 0.55873
## Week_39 1973.64 2039.79 0.968 0.37063
## Week_40 -761.51 2331.13 -0.327 0.75501
## Week_41 -2030.78 2302.22 -0.882 0.41167
## Week_42 -1113.27 2847.16 -0.391 0.70930
## Week_43 1810.92 3104.29 0.583 0.58090
## Week_44 1513.11 1344.14 1.126 0.30329
## Week_45 -3075.01 2172.68 -1.415 0.20673
## Week_46 -537.24 1668.22 -0.322 0.75835
## Week_47 1197.76 1521.02 0.787 0.46097
## Week_48 320.67 1242.05 0.258 0.80490
## Week_49 -1484.16 1164.92 -1.274 0.24977
## Week_50 2038.08 2029.22 1.004 0.35397
## Week_51 951.15 1378.33 0.690 0.51594
## Week_52 1096.07 1148.33 0.954 0.37669
## Week_53 -1152.40 925.95 -1.245 0.25970
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12820 on 6 degrees of freedom
## (2 observations deleted due to missingness)
## Multiple R-squared: 0.953, Adjusted R-squared: 0.5378
## F-statistic: 2.295 on 53 and 6 DF, p-value: 0.1483
Abbotsford monthly
## [1] "There are 6 NA in the matrix X in Abbotsford station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -83128 -40055 -1379 28889 110283
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 139811.0 7999.8 17.477 <2e-16 ***
## Month_1 521.0 884.1 0.589 0.5583
## Month_2 -913.1 1016.1 -0.899 0.3732
## Month_3 997.3 785.2 1.270 0.2101
## Month_4 1051.4 607.8 1.730 0.0900 .
## Month_5 936.8 511.1 1.833 0.0729 .
## Month_6 621.2 320.9 1.936 0.0587 .
## Month_7 1063.9 478.5 2.223 0.0308 *
## Month_8 1917.5 1178.1 1.628 0.1100
## Month_9 4248.3 1656.4 2.565 0.0134 *
## Month_10 -2634.4 2914.7 -0.904 0.3705
## Month_11 -1132.8 2020.3 -0.561 0.5776
## Month_12 415.0 1048.2 0.396 0.6939
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 47600 on 49 degrees of freedom
## Multiple R-squared: 0.4567, Adjusted R-squared: 0.3237
## F-statistic: 3.433 on 12 and 49 DF, p-value: 0.001068
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10085.2 -3371.7 504.3 3570.7 11400.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 24425.49 919.85 26.554 <2e-16 ***
## Month_1 -49.89 101.66 -0.491 0.6258
## Month_2 -29.44 116.83 -0.252 0.8021
## Month_3 199.03 90.29 2.204 0.0322 *
## Month_4 120.83 69.89 1.729 0.0901 .
## Month_5 97.11 58.77 1.652 0.1048
## Month_6 18.59 36.90 0.504 0.6167
## Month_7 63.99 55.02 1.163 0.2505
## Month_8 311.02 135.46 2.296 0.0260 *
## Month_9 339.10 190.46 1.780 0.0812 .
## Month_10 -445.52 335.15 -1.329 0.1899
## Month_11 -236.64 232.31 -1.019 0.3134
## Month_12 54.12 120.53 0.449 0.6554
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5474 on 49 degrees of freedom
## Multiple R-squared: 0.3811, Adjusted R-squared: 0.2296
## F-statistic: 2.515 on 12 and 49 DF, p-value: 0.01158
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -31122 -8239 -518 7236 32357
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 60095.97 2409.55 24.941 <2e-16 ***
## Month_1 191.94 266.29 0.721 0.4745
## Month_2 -270.34 306.04 -0.883 0.3814
## Month_3 383.27 236.50 1.621 0.1115
## Month_4 244.95 183.08 1.338 0.1871
## Month_5 179.89 153.95 1.169 0.2483
## Month_6 242.49 96.66 2.509 0.0155 *
## Month_7 369.64 144.12 2.565 0.0134 *
## Month_8 912.49 354.85 2.572 0.0132 *
## Month_9 934.74 498.91 1.874 0.0670 .
## Month_10 -1069.26 877.91 -1.218 0.2291
## Month_11 -405.27 608.52 -0.666 0.5085
## Month_12 359.04 315.73 1.137 0.2610
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14340 on 49 degrees of freedom
## Multiple R-squared: 0.493, Adjusted R-squared: 0.3689
## F-statistic: 3.971 on 12 and 49 DF, p-value: 0.0002775
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -16719.9 -4951.4 841.6 4278.2 14175.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 92702.49 1276.14 72.643 < 2e-16 ***
## Month_1 125.12 141.03 0.887 0.379328
## Month_2 -19.87 162.09 -0.123 0.902953
## Month_3 330.37 125.26 2.638 0.011158 *
## Month_4 115.13 96.96 1.187 0.240819
## Month_5 -77.89 81.53 -0.955 0.344081
## Month_6 14.04 51.19 0.274 0.785021
## Month_7 301.68 76.33 3.953 0.000248 ***
## Month_8 -233.37 187.93 -1.242 0.220240
## Month_9 329.03 264.23 1.245 0.218975
## Month_10 -398.92 464.96 -0.858 0.395088
## Month_11 745.00 322.28 2.312 0.025044 *
## Month_12 -89.07 167.22 -0.533 0.596675
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7594 on 49 degrees of freedom
## Multiple R-squared: 0.4863, Adjusted R-squared: 0.3605
## F-statistic: 3.865 on 12 and 49 DF, p-value: 0.0003605
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12660.6 -3094.1 227.8 2645.3 12989.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 19311.52 958.64 20.145 <2e-16 ***
## Month_1 -32.93 105.94 -0.311 0.7572
## Month_2 -66.48 121.76 -0.546 0.5876
## Month_3 142.65 94.09 1.516 0.1359
## Month_4 93.74 72.84 1.287 0.2042
## Month_5 110.53 61.25 1.805 0.0773 .
## Month_6 49.61 38.45 1.290 0.2030
## Month_7 68.37 57.34 1.192 0.2388
## Month_8 370.36 141.18 2.623 0.0116 *
## Month_9 246.75 198.49 1.243 0.2197
## Month_10 -445.42 349.28 -1.275 0.2082
## Month_11 -217.27 242.10 -0.897 0.3739
## Month_12 102.03 125.61 0.812 0.4206
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5705 on 49 degrees of freedom
## Multiple R-squared: 0.3678, Adjusted R-squared: 0.213
## F-statistic: 2.376 on 12 and 49 DF, p-value: 0.01669
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11931.2 -3416.9 40.2 2467.4 17139.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 27981.612 1068.006 26.200 <2e-16 ***
## Month_1 -134.482 118.031 -1.139 0.2601
## Month_2 -140.207 135.650 -1.034 0.3064
## Month_3 128.518 104.827 1.226 0.2261
## Month_4 -4.936 81.148 -0.061 0.9517
## Month_5 63.461 68.235 0.930 0.3569
## Month_6 24.973 42.841 0.583 0.5626
## Month_7 -11.757 63.879 -0.184 0.8547
## Month_8 274.108 157.282 1.743 0.0876 .
## Month_9 95.019 221.137 0.430 0.6693
## Month_10 177.198 389.125 0.455 0.6509
## Month_11 114.656 269.721 0.425 0.6726
## Month_12 84.667 139.945 0.605 0.5480
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6355 on 49 degrees of freedom
## Multiple R-squared: 0.1769, Adjusted R-squared: -0.02462
## F-statistic: 0.8778 on 12 and 49 DF, p-value: 0.5741
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -31537 -7471 2092 9153 29061
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 67700.54 2429.09 27.871 < 2e-16 ***
## Month_1 -125.34 268.45 -0.467 0.64264
## Month_2 -66.19 308.52 -0.215 0.83103
## Month_3 302.17 238.42 1.267 0.21101
## Month_4 286.12 184.56 1.550 0.12752
## Month_5 52.63 155.20 0.339 0.73598
## Month_6 4.35 97.44 0.045 0.96458
## Month_7 -46.82 145.29 -0.322 0.74861
## Month_8 594.42 357.73 1.662 0.10296
## Month_9 1551.98 502.96 3.086 0.00334 **
## Month_10 -1242.53 885.03 -1.404 0.16664
## Month_11 264.68 613.46 0.431 0.66803
## Month_12 -208.75 318.29 -0.656 0.51499
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14450 on 49 degrees of freedom
## Multiple R-squared: 0.3792, Adjusted R-squared: 0.2272
## F-statistic: 2.495 on 12 and 49 DF, p-value: 0.01222
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -17820.0 -6968.2 -405.4 5302.3 20617.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 43135.53 1619.08 26.642 <2e-16 ***
## Month_1 -44.55 178.93 -0.249 0.8044
## Month_2 47.11 205.64 0.229 0.8198
## Month_3 207.05 158.92 1.303 0.1987
## Month_4 98.80 123.02 0.803 0.4258
## Month_5 130.06 103.44 1.257 0.2146
## Month_6 10.29 64.95 0.159 0.8747
## Month_7 11.01 96.84 0.114 0.9099
## Month_8 263.14 238.44 1.104 0.2752
## Month_9 599.14 335.24 1.787 0.0801 .
## Month_10 -107.63 589.91 -0.182 0.8560
## Month_11 -349.29 408.89 -0.854 0.3971
## Month_12 15.50 212.15 0.073 0.9421
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9635 on 49 degrees of freedom
## Multiple R-squared: 0.1837, Adjusted R-squared: -0.01622
## F-statistic: 0.9188 on 12 and 49 DF, p-value: 0.5357
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27165 -9654 295 7836 37911
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 42305.30 2599.62 16.274 < 2e-16 ***
## Month_1 92.96 287.30 0.324 0.74764
## Month_2 -190.45 330.18 -0.577 0.56672
## Month_3 570.16 255.16 2.235 0.03004 *
## Month_4 244.04 197.52 1.236 0.22253
## Month_5 198.78 166.09 1.197 0.23713
## Month_6 202.15 104.28 1.939 0.05833 .
## Month_7 239.27 155.49 1.539 0.13027
## Month_8 803.04 382.84 2.098 0.04112 *
## Month_9 1796.15 538.27 3.337 0.00162 **
## Month_10 -1200.40 947.16 -1.267 0.21102
## Month_11 74.77 656.52 0.114 0.90979
## Month_12 263.92 340.64 0.775 0.44219
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15470 on 49 degrees of freedom
## Multiple R-squared: 0.5022, Adjusted R-squared: 0.3803
## F-statistic: 4.12 on 12 and 49 DF, p-value: 0.0001929
Kelowna monthly
## [1] "There are 7 NA in the matrix X in Kelowna station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -97125 -39427 -8252 36192 95814
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 166461.3 9204.8 18.084 <2e-16 ***
## Month_1 -584.5 1010.2 -0.579 0.566
## Month_2 -1794.7 1137.4 -1.578 0.121
## Month_3 1236.4 917.6 1.347 0.184
## Month_4 -183.6 1047.9 -0.175 0.862
## Month_5 654.3 617.5 1.060 0.295
## Month_6 441.2 569.6 0.775 0.442
## Month_7 235.5 1024.4 0.230 0.819
## Month_8 5077.8 3179.3 1.597 0.117
## Month_9 6652.6 3152.1 2.111 0.040 *
## Month_10 -3069.9 3334.4 -0.921 0.362
## Month_11 418.4 1427.3 0.293 0.771
## Month_12 -453.8 994.0 -0.457 0.650
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 53640 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3101, Adjusted R-squared: 0.1377
## F-statistic: 1.798 on 12 and 48 DF, p-value: 0.0755
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11224.6 -3693.7 300.7 3662.8 11372.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 26403.302 948.583 27.834 <2e-16 ***
## Month_1 -200.357 104.108 -1.925 0.0602 .
## Month_2 -223.187 117.207 -1.904 0.0629 .
## Month_3 174.251 94.562 1.843 0.0716 .
## Month_4 -38.479 107.990 -0.356 0.7232
## Month_5 112.974 63.637 1.775 0.0822 .
## Month_6 1.435 58.699 0.024 0.9806
## Month_7 -28.891 105.571 -0.274 0.7855
## Month_8 669.822 327.639 2.044 0.0464 *
## Month_9 433.011 324.832 1.333 0.1888
## Month_10 -215.774 343.622 -0.628 0.5330
## Month_11 -84.118 147.083 -0.572 0.5701
## Month_12 -12.822 102.433 -0.125 0.9009
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5528 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3804, Adjusted R-squared: 0.2255
## F-statistic: 2.455 on 12 and 48 DF, p-value: 0.01382
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -31413 -12170 -2894 9570 31001
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 68017.23 2788.52 24.392 <2e-16 ***
## Month_1 -367.68 306.04 -1.201 0.2355
## Month_2 -626.16 344.55 -1.817 0.0754 .
## Month_3 559.18 277.98 2.012 0.0499 *
## Month_4 -273.11 317.45 -0.860 0.3939
## Month_5 144.34 187.07 0.772 0.4442
## Month_6 168.89 172.56 0.979 0.3326
## Month_7 350.62 310.34 1.130 0.2642
## Month_8 1469.29 963.15 1.526 0.1337
## Month_9 1916.71 954.90 2.007 0.0504 .
## Month_10 -343.77 1010.13 -0.340 0.7351
## Month_11 73.32 432.38 0.170 0.8661
## Month_12 78.94 301.12 0.262 0.7943
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 16250 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3577, Adjusted R-squared: 0.1971
## F-statistic: 2.227 on 12 and 48 DF, p-value: 0.02505
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14153 -5490 -1262 5376 22646
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 94200.881 1622.263 58.068 <2e-16 ***
## Month_1 54.751 178.045 0.308 0.760
## Month_2 -165.778 200.447 -0.827 0.412
## Month_3 157.115 161.720 0.972 0.336
## Month_4 78.341 184.683 0.424 0.673
## Month_5 4.315 108.833 0.040 0.969
## Month_6 -113.398 100.387 -1.130 0.264
## Month_7 208.230 180.547 1.153 0.254
## Month_8 574.145 560.326 1.025 0.311
## Month_9 182.230 555.527 0.328 0.744
## Month_10 -940.413 587.661 -1.600 0.116
## Month_11 347.187 251.542 1.380 0.174
## Month_12 -104.652 175.180 -0.597 0.553
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9453 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.2174, Adjusted R-squared: 0.02179
## F-statistic: 1.111 on 12 and 48 DF, p-value: 0.3733
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11209.8 -3796.6 -377.4 3152.6 15151.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 21464.44 1038.86 20.662 <2e-16 ***
## Month_1 -140.29 114.02 -1.230 0.2245
## Month_2 -213.08 128.36 -1.660 0.1034
## Month_3 180.26 103.56 1.741 0.0882 .
## Month_4 -174.68 118.27 -1.477 0.1462
## Month_5 54.74 69.69 0.785 0.4361
## Month_6 54.42 64.29 0.847 0.4015
## Month_7 -18.26 115.62 -0.158 0.8752
## Month_8 512.06 358.82 1.427 0.1600
## Month_9 610.33 355.75 1.716 0.0927 .
## Month_10 -258.02 376.32 -0.686 0.4962
## Month_11 -74.84 161.08 -0.465 0.6443
## Month_12 -17.72 112.18 -0.158 0.8751
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6054 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3007, Adjusted R-squared: 0.1259
## F-statistic: 1.72 on 12 and 48 DF, p-value: 0.09187
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13918.5 -3792.6 -126.6 1995.7 16782.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 29365.79 1131.82 25.946 <2e-16 ***
## Month_1 -107.59 124.22 -0.866 0.391
## Month_2 -88.39 139.85 -0.632 0.530
## Month_3 83.94 112.83 0.744 0.461
## Month_4 48.09 128.85 0.373 0.711
## Month_5 -77.52 75.93 -1.021 0.312
## Month_6 112.42 70.04 1.605 0.115
## Month_7 -23.60 125.96 -0.187 0.852
## Month_8 236.91 390.93 0.606 0.547
## Month_9 166.80 387.58 0.430 0.669
## Month_10 172.64 410.00 0.421 0.676
## Month_11 -107.09 175.50 -0.610 0.545
## Month_12 28.53 122.22 0.233 0.816
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6595 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.1298, Adjusted R-squared: -0.08779
## F-statistic: 0.5965 on 12 and 48 DF, p-value: 0.8341
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -37202 -7839 1099 8652 23218
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 71851.85 2561.83 28.047 <2e-16 ***
## Month_1 -405.20 281.16 -1.441 0.1560
## Month_2 -577.77 316.54 -1.825 0.0742 .
## Month_3 14.96 255.38 0.059 0.9535
## Month_4 344.61 291.65 1.182 0.2432
## Month_5 341.17 171.87 1.985 0.0529 .
## Month_6 25.43 158.53 0.160 0.8732
## Month_7 -184.93 285.11 -0.649 0.5197
## Month_8 2262.38 884.85 2.557 0.0138 *
## Month_9 899.62 877.27 1.025 0.3103
## Month_10 -255.89 928.02 -0.276 0.7839
## Month_11 410.47 397.23 1.033 0.3066
## Month_12 42.58 276.64 0.154 0.8783
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14930 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3514, Adjusted R-squared: 0.1892
## F-statistic: 2.167 on 12 and 48 DF, p-value: 0.02931
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14682.6 -7423.7 -193.1 6081.1 18921.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 45912.01 1489.48 30.824 < 2e-16 ***
## Month_1 -162.22 163.47 -0.992 0.32600
## Month_2 -150.52 184.04 -0.818 0.41748
## Month_3 162.41 148.48 1.094 0.27950
## Month_4 350.11 169.57 2.065 0.04437 *
## Month_5 269.45 99.92 2.697 0.00963 **
## Month_6 -36.11 92.17 -0.392 0.69699
## Month_7 -17.82 165.77 -0.107 0.91485
## Month_8 224.31 514.46 0.436 0.66479
## Month_9 463.59 510.06 0.909 0.36794
## Month_10 546.11 539.56 1.012 0.31655
## Month_11 42.36 230.95 0.183 0.85524
## Month_12 -178.26 160.84 -1.108 0.27326
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8679 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.335, Adjusted R-squared: 0.1687
## F-statistic: 2.015 on 12 and 48 DF, p-value: 0.04345
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -36558 -7983 -761 7877 32691
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 50249.40 2897.35 17.343 <2e-16 ***
## Month_1 -353.10 317.99 -1.110 0.2723
## Month_2 -753.93 358.00 -2.106 0.0405 *
## Month_3 344.17 288.83 1.192 0.2393
## Month_4 -26.56 329.84 -0.081 0.9362
## Month_5 393.99 194.37 2.027 0.0482 *
## Month_6 137.54 179.29 0.767 0.4468
## Month_7 183.98 322.45 0.571 0.5710
## Month_8 2159.48 1000.74 2.158 0.0360 *
## Month_9 2334.12 992.17 2.353 0.0228 *
## Month_10 -803.95 1049.56 -0.766 0.4474
## Month_11 321.73 449.25 0.716 0.4774
## Month_12 190.80 312.87 0.610 0.5448
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 16880 on 48 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.4155, Adjusted R-squared: 0.2694
## F-statistic: 2.844 on 12 and 48 DF, p-value: 0.005024
FortStJohn monthly
## [1] "There are 5 NA in the matrix X in FortStJoh station"
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -79652 -43998 -14534 46262 110352
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 164908.19 9397.31 17.548 <2e-16 ***
## Month_1 73.09 263.57 0.277 0.783
## Month_2 206.15 477.12 0.432 0.668
## Month_3 14.85 616.14 0.024 0.981
## Month_4 443.26 507.29 0.874 0.386
## Month_5 -83.92 693.65 -0.121 0.904
## Month_6 648.67 503.84 1.287 0.204
## Month_7 565.91 1053.46 0.537 0.594
## Month_8 813.54 2055.87 0.396 0.694
## Month_9 1399.99 1566.74 0.894 0.376
## Month_10 -2174.33 1898.68 -1.145 0.258
## Month_11 -48.21 768.93 -0.063 0.950
## Month_12 207.48 371.07 0.559 0.579
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 60380 on 49 degrees of freedom
## Multiple R-squared: 0.1261, Adjusted R-squared: -0.08794
## F-statistic: 0.5891 on 12 and 49 DF, p-value: 0.8403
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10531.8 -4254.7 -618.8 3653.1 13275.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 27029.7410 1006.0030 26.868 <2e-16 ***
## Month_1 -0.4965 28.2157 -0.018 0.986
## Month_2 -20.3518 51.0763 -0.398 0.692
## Month_3 77.6953 65.9595 1.178 0.245
## Month_4 87.1528 54.3066 1.605 0.115
## Month_5 -48.5952 74.2567 -0.654 0.516
## Month_6 -7.8296 53.9371 -0.145 0.885
## Month_7 28.8305 112.7754 0.256 0.799
## Month_8 -48.1397 220.0858 -0.219 0.828
## Month_9 185.4445 167.7225 1.106 0.274
## Month_10 -75.7669 203.2578 -0.373 0.711
## Month_11 -59.2748 82.3161 -0.720 0.475
## Month_12 27.4565 39.7243 0.691 0.493
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6463 on 49 degrees of freedom
## Multiple R-squared: 0.1371, Adjusted R-squared: -0.07417
## F-statistic: 0.649 on 12 and 49 DF, p-value: 0.7898
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -24767 -13776 -3217 12260 33190
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 67543.57 2813.95 24.003 <2e-16 ***
## Month_1 31.62 78.92 0.401 0.6905
## Month_2 -29.08 142.87 -0.204 0.8395
## Month_3 -14.36 184.50 -0.078 0.9383
## Month_4 277.38 151.90 1.826 0.0739 .
## Month_5 -23.04 207.71 -0.111 0.9121
## Month_6 264.73 150.87 1.755 0.0856 .
## Month_7 355.82 315.45 1.128 0.2648
## Month_8 339.49 615.62 0.551 0.5838
## Month_9 394.50 469.15 0.841 0.4045
## Month_10 -544.73 568.54 -0.958 0.3427
## Month_11 -55.79 230.25 -0.242 0.8096
## Month_12 26.34 111.12 0.237 0.8136
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 18080 on 49 degrees of freedom
## Multiple R-squared: 0.194, Adjusted R-squared: -0.003383
## F-statistic: 0.9829 on 12 and 49 DF, p-value: 0.478
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -18939 -5971 -1971 7355 19588
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 93855.265 1543.634 60.801 <2e-16 ***
## Month_1 -22.834 43.295 -0.527 0.600
## Month_2 -14.105 78.373 -0.180 0.858
## Month_3 92.711 101.210 0.916 0.364
## Month_4 -66.526 83.329 -0.798 0.429
## Month_5 -72.265 113.941 -0.634 0.529
## Month_6 62.739 82.762 0.758 0.452
## Month_7 130.013 173.045 0.751 0.456
## Month_8 -312.848 337.705 -0.926 0.359
## Month_9 53.473 257.357 0.208 0.836
## Month_10 -395.751 311.883 -1.269 0.210
## Month_11 3.651 126.308 0.029 0.977
## Month_12 -44.120 60.954 -0.724 0.473
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9918 on 49 degrees of freedom
## Multiple R-squared: 0.1238, Adjusted R-squared: -0.09081
## F-statistic: 0.5768 on 12 and 49 DF, p-value: 0.85
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9887 -4263 -1435 3835 15253
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 21688.005 1057.300 20.513 <2e-16 ***
## Month_1 6.936 29.654 0.234 0.816
## Month_2 -35.909 53.681 -0.669 0.507
## Month_3 46.301 69.323 0.668 0.507
## Month_4 83.593 57.076 1.465 0.149
## Month_5 -24.932 78.043 -0.319 0.751
## Month_6 30.518 56.687 0.538 0.593
## Month_7 39.670 118.526 0.335 0.739
## Month_8 32.964 231.308 0.143 0.887
## Month_9 141.447 176.275 0.802 0.426
## Month_10 -163.093 213.622 -0.763 0.449
## Month_11 -49.570 86.513 -0.573 0.569
## Month_12 5.235 41.750 0.125 0.901
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6793 on 49 degrees of freedom
## Multiple R-squared: 0.1036, Adjusted R-squared: -0.116
## F-statistic: 0.4718 on 12 and 49 DF, p-value: 0.9216
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11684 -3339 -533 1686 17547
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 28864.199 1064.988 27.103 <2e-16 ***
## Month_1 13.427 29.870 0.450 0.655
## Month_2 -23.007 54.071 -0.425 0.672
## Month_3 44.791 69.827 0.641 0.524
## Month_4 13.052 57.491 0.227 0.821
## Month_5 46.588 78.611 0.593 0.556
## Month_6 40.467 57.100 0.709 0.482
## Month_7 34.767 119.388 0.291 0.772
## Month_8 -55.753 232.990 -0.239 0.812
## Month_9 71.991 177.557 0.405 0.687
## Month_10 -25.244 215.175 -0.117 0.907
## Month_11 -4.372 87.142 -0.050 0.960
## Month_12 -16.184 42.053 -0.385 0.702
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6842 on 49 degrees of freedom
## Multiple R-squared: 0.04597, Adjusted R-squared: -0.1877
## F-statistic: 0.1967 on 12 and 49 DF, p-value: 0.998
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -33266 -7118 1448 8605 33226
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 71250.67 2506.95 28.421 <2e-16 ***
## Month_1 -125.53 70.31 -1.785 0.0804 .
## Month_2 65.39 127.28 0.514 0.6097
## Month_3 84.00 164.37 0.511 0.6116
## Month_4 165.39 135.33 1.222 0.2275
## Month_5 -170.25 185.05 -0.920 0.3621
## Month_6 113.98 134.41 0.848 0.4006
## Month_7 -62.84 281.04 -0.224 0.8240
## Month_8 259.13 548.45 0.472 0.6387
## Month_9 200.94 417.96 0.481 0.6328
## Month_10 -502.21 506.52 -0.991 0.3263
## Month_11 -373.49 205.13 -1.821 0.0748 .
## Month_12 111.24 98.99 1.124 0.2666
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 16110 on 49 degrees of freedom
## Multiple R-squared: 0.2292, Adjusted R-squared: 0.04047
## F-statistic: 1.214 on 12 and 49 DF, p-value: 0.3005
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -17783.7 -7321.2 -279.2 6605.6 19913.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 45849.4139 1569.5933 29.211 <2e-16 ***
## Month_1 35.1143 44.0228 0.798 0.429
## Month_2 53.1092 79.6906 0.666 0.508
## Month_3 -9.9611 102.9117 -0.097 0.923
## Month_4 77.6044 84.7307 0.916 0.364
## Month_5 36.2146 115.8573 0.313 0.756
## Month_6 0.6290 84.1541 0.007 0.994
## Month_7 40.4917 175.9553 0.230 0.819
## Month_8 85.6888 343.3838 0.250 0.804
## Month_9 157.5987 261.6852 0.602 0.550
## Month_10 0.9095 317.1284 0.003 0.998
## Month_11 -60.4780 128.4318 -0.471 0.640
## Month_12 82.5281 61.9789 1.332 0.189
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10080 on 49 degrees of freedom
## Multiple R-squared: 0.1057, Adjusted R-squared: -0.1133
## F-statistic: 0.4826 on 12 and 49 DF, p-value: 0.9153
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -34295 -13879 -1044 9909 44912
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 51035.224 3185.986 16.019 <2e-16 ***
## Month_1 -4.289 89.358 -0.048 0.9619
## Month_2 107.102 161.757 0.662 0.5110
## Month_3 131.357 208.892 0.629 0.5324
## Month_4 120.942 171.988 0.703 0.4853
## Month_5 -75.278 235.169 -0.320 0.7503
## Month_6 340.313 170.817 1.992 0.0519 .
## Month_7 14.794 357.157 0.041 0.9671
## Month_8 -64.264 697.006 -0.092 0.9269
## Month_9 546.313 531.173 1.029 0.3088
## Month_10 -373.816 643.712 -0.581 0.5641
## Month_11 -62.687 260.693 -0.240 0.8110
## Month_12 50.618 125.806 0.402 0.6892
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 20470 on 49 degrees of freedom
## Multiple R-squared: 0.1284, Adjusted R-squared: -0.08503
## F-statistic: 0.6016 on 12 and 49 DF, p-value: 0.8301
linear reg for yield VS weekly Max Temp
Abbotsford
## [1] "Results for crop: Apples"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27887.8 -8791.8 -970.2 9462.8 30817.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -379410.47 216422.90 -1.753 0.1177
## Week_1 5569.15 3867.69 1.440 0.1879
## Week_2 4633.31 4580.18 1.012 0.3413
## Week_3 -3710.64 4951.29 -0.749 0.4751
## Week_4 27.95 4122.76 0.007 0.9948
## Week_5 487.06 4704.67 0.104 0.9201
## Week_6 -1109.62 6349.16 -0.175 0.8656
## Week_7 2491.88 5178.18 0.481 0.6432
## Week_8 1956.54 8225.02 0.238 0.8180
## Week_9 -2324.53 4514.65 -0.515 0.6206
## Week_10 -3040.07 7166.04 -0.424 0.6826
## Week_11 -15492.00 11097.32 -1.396 0.2002
## Week_12 6499.98 7199.61 0.903 0.3930
## Week_13 8247.42 11298.69 0.730 0.4862
## Week_14 -9458.74 16998.02 -0.556 0.5931
## Week_15 8600.07 10328.70 0.833 0.4292
## Week_16 -1342.51 6477.99 -0.207 0.8410
## Week_17 11582.98 7095.79 1.632 0.1412
## Week_18 6484.74 7605.25 0.853 0.4186
## Week_19 1256.56 6470.79 0.194 0.8509
## Week_20 7659.30 7092.90 1.080 0.3117
## Week_21 2722.31 7773.04 0.350 0.7352
## Week_22 -4391.71 7022.84 -0.625 0.5492
## Week_23 181.00 6893.98 0.026 0.9797
## Week_24 -7746.16 6029.18 -1.285 0.2348
## Week_25 2684.34 7933.91 0.338 0.7438
## Week_26 1207.84 7960.36 0.152 0.8832
## Week_27 10662.66 11377.60 0.937 0.3761
## Week_28 3922.51 9126.18 0.430 0.6787
## Week_29 -12120.23 9269.33 -1.308 0.2273
## Week_30 8497.35 8158.22 1.042 0.3281
## Week_31 10183.10 7471.30 1.363 0.2100
## Week_32 -6251.69 4441.55 -1.408 0.1969
## Week_33 -12660.54 8296.48 -1.526 0.1655
## Week_34 24884.44 8528.16 2.918 0.0194 *
## Week_35 -4741.30 5859.62 -0.809 0.4418
## Week_36 3778.39 7869.29 0.480 0.6440
## Week_37 2959.59 9376.17 0.316 0.7603
## Week_38 477.54 8461.64 0.056 0.9564
## Week_39 -11950.24 8350.59 -1.431 0.1903
## Week_40 6703.27 7324.00 0.915 0.3868
## Week_41 -10685.91 8618.50 -1.240 0.2502
## Week_42 8432.17 8595.78 0.981 0.3553
## Week_43 1782.38 6710.56 0.266 0.7973
## Week_44 -4602.96 4994.26 -0.922 0.3837
## Week_45 -10205.91 7467.38 -1.367 0.2089
## Week_46 9118.57 6963.67 1.309 0.2267
## Week_47 -2333.68 4243.52 -0.550 0.5974
## Week_48 751.76 7298.11 0.103 0.9205
## Week_49 697.45 3835.69 0.182 0.8602
## Week_50 -2093.30 4034.65 -0.519 0.6179
## Week_51 -4463.51 4658.36 -0.958 0.3660
## Week_52 6020.65 6413.27 0.939 0.3753
## Week_53 -1509.30 3352.33 -0.450 0.6645
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 39000 on 8 degrees of freedom
## Multiple R-squared: 0.9405, Adjusted R-squared: 0.5459
## F-statistic: 2.384 on 53 and 8 DF, p-value: 0.09579
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4204.1 -1123.1 117.2 1306.2 3614.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -13226.592 28152.253 -0.470 0.6510
## Week_1 -206.202 503.109 -0.410 0.6927
## Week_2 471.703 595.789 0.792 0.4514
## Week_3 -430.418 644.063 -0.668 0.5228
## Week_4 460.727 536.288 0.859 0.4153
## Week_5 -353.637 611.982 -0.578 0.5793
## Week_6 861.448 825.897 1.043 0.3274
## Week_7 267.191 673.576 0.397 0.7020
## Week_8 -383.405 1069.908 -0.358 0.7294
## Week_9 484.765 587.265 0.825 0.4330
## Week_10 -2000.691 932.157 -2.146 0.0641 .
## Week_11 -971.361 1443.538 -0.673 0.5200
## Week_12 1229.279 936.524 1.313 0.2257
## Week_13 -672.262 1469.731 -0.457 0.6595
## Week_14 -642.650 2211.100 -0.291 0.7787
## Week_15 2896.384 1343.555 2.156 0.0632 .
## Week_16 -314.541 842.656 -0.373 0.7186
## Week_17 1648.437 923.019 1.786 0.1119
## Week_18 755.261 989.290 0.763 0.4671
## Week_19 1460.848 841.719 1.736 0.1209
## Week_20 550.243 922.643 0.596 0.5674
## Week_21 -2.594 1011.116 -0.003 0.9980
## Week_22 959.620 913.529 1.050 0.3242
## Week_23 -113.083 896.768 -0.126 0.9028
## Week_24 -1104.231 784.275 -1.408 0.1968
## Week_25 -914.571 1032.042 -0.886 0.4014
## Week_26 772.857 1035.482 0.746 0.4768
## Week_27 1194.739 1479.997 0.807 0.4429
## Week_28 -243.264 1187.132 -0.205 0.8428
## Week_29 -2210.946 1205.753 -1.834 0.1041
## Week_30 265.191 1061.220 0.250 0.8090
## Week_31 226.036 971.866 0.233 0.8219
## Week_32 515.944 577.756 0.893 0.3979
## Week_33 -795.922 1079.205 -0.738 0.4819
## Week_34 3514.440 1109.341 3.168 0.0132 *
## Week_35 -396.296 762.219 -0.520 0.6172
## Week_36 -1025.491 1023.636 -1.002 0.3458
## Week_37 -345.374 1219.650 -0.283 0.7842
## Week_38 1584.012 1100.689 1.439 0.1881
## Week_39 -1461.904 1086.243 -1.346 0.2152
## Week_40 778.879 952.705 0.818 0.4373
## Week_41 -1850.641 1121.093 -1.651 0.1374
## Week_42 -3.340 1118.138 -0.003 0.9977
## Week_43 40.480 872.908 0.046 0.9641
## Week_44 -631.555 649.653 -0.972 0.3595
## Week_45 -2162.071 971.355 -2.226 0.0567 .
## Week_46 1061.800 905.833 1.172 0.2748
## Week_47 -344.553 551.996 -0.624 0.5499
## Week_48 -614.060 949.336 -0.647 0.5359
## Week_49 90.030 498.946 0.180 0.8613
## Week_50 125.258 524.826 0.239 0.8174
## Week_51 -41.222 605.959 -0.068 0.9474
## Week_52 634.156 834.237 0.760 0.4690
## Week_53 -183.356 436.071 -0.420 0.6852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5074 on 8 degrees of freedom
## Multiple R-squared: 0.9132, Adjusted R-squared: 0.3381
## F-statistic: 1.588 on 53 and 8 DF, p-value: 0.2509
## [1] "Results for crop: Maize (corn)"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8212.3 -3126.3 -288.8 2799.6 7937.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -95390.10 59691.64 -1.598 0.1487
## Week_1 750.61 1066.75 0.704 0.5016
## Week_2 1107.53 1263.26 0.877 0.4062
## Week_3 -1040.10 1365.62 -0.762 0.4681
## Week_4 1237.90 1137.10 1.089 0.3080
## Week_5 -1064.53 1297.60 -0.820 0.4358
## Week_6 594.68 1751.16 0.340 0.7429
## Week_7 530.56 1428.19 0.371 0.7199
## Week_8 366.48 2268.54 0.162 0.8757
## Week_9 -624.03 1245.19 -0.501 0.6298
## Week_10 -2899.75 1976.47 -1.467 0.1805
## Week_11 -4937.88 3060.75 -1.613 0.1453
## Week_12 1578.46 1985.73 0.795 0.4496
## Week_13 2252.13 3116.29 0.723 0.4905
## Week_14 -2017.69 4688.23 -0.430 0.6783
## Week_15 2250.45 2848.76 0.790 0.4523
## Week_16 447.49 1786.70 0.250 0.8085
## Week_17 4306.02 1957.09 2.200 0.0590 .
## Week_18 1908.14 2097.61 0.910 0.3896
## Week_19 991.73 1784.71 0.556 0.5936
## Week_20 1918.57 1956.29 0.981 0.3555
## Week_21 -42.95 2143.88 -0.020 0.9845
## Week_22 168.93 1936.97 0.087 0.9326
## Week_23 -510.02 1901.43 -0.268 0.7953
## Week_24 -2308.19 1662.91 -1.388 0.2026
## Week_25 -978.05 2188.25 -0.447 0.6668
## Week_26 1289.66 2195.55 0.587 0.5731
## Week_27 4283.96 3138.06 1.365 0.2094
## Week_28 1816.04 2517.09 0.721 0.4912
## Week_29 -3301.41 2556.58 -1.291 0.2326
## Week_30 2132.15 2250.12 0.948 0.3711
## Week_31 1333.15 2060.66 0.647 0.5358
## Week_32 -970.70 1225.02 -0.792 0.4510
## Week_33 -2056.35 2288.25 -0.899 0.3951
## Week_34 7513.20 2352.15 3.194 0.0127 *
## Week_35 -2363.57 1616.14 -1.462 0.1818
## Week_36 1555.51 2170.43 0.717 0.4940
## Week_37 -1101.11 2586.04 -0.426 0.6815
## Week_38 1467.94 2333.81 0.629 0.5469
## Week_39 -4355.88 2303.18 -1.891 0.0952 .
## Week_40 1979.71 2020.03 0.980 0.3558
## Week_41 -2932.57 2377.07 -1.234 0.2523
## Week_42 2021.47 2370.80 0.853 0.4186
## Week_43 -137.38 1850.84 -0.074 0.9427
## Week_44 -533.27 1377.47 -0.387 0.7087
## Week_45 -4128.94 2059.58 -2.005 0.0799 .
## Week_46 3252.47 1920.65 1.693 0.1288
## Week_47 -977.19 1170.40 -0.835 0.4280
## Week_48 55.03 2012.89 0.027 0.9789
## Week_49 -99.20 1057.92 -0.094 0.9276
## Week_50 303.35 1112.80 0.273 0.7921
## Week_51 -1293.32 1284.82 -1.007 0.3436
## Week_52 2003.27 1768.85 1.133 0.2902
## Week_53 -1053.95 924.61 -1.140 0.2873
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10760 on 8 degrees of freedom
## Multiple R-squared: 0.9534, Adjusted R-squared: 0.6447
## F-statistic: 3.089 on 53 and 8 DF, p-value: 0.04663
## [1] "Results for crop: Peaches and nectarines"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5074.5 -1479.5 83.5 1702.3 5149.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2186.260 31963.754 -0.068 0.9471
## Week_1 934.411 571.224 1.636 0.1405
## Week_2 -5.987 676.452 -0.009 0.9932
## Week_3 -303.844 731.262 -0.416 0.6887
## Week_4 -341.289 608.895 -0.561 0.5905
## Week_5 -19.539 694.838 -0.028 0.9783
## Week_6 -437.527 937.715 -0.467 0.6532
## Week_7 -468.809 764.771 -0.613 0.5569
## Week_8 -149.493 1214.762 -0.123 0.9051
## Week_9 -3.953 666.774 -0.006 0.9954
## Week_10 -192.018 1058.361 -0.181 0.8605
## Week_11 -120.229 1638.977 -0.073 0.9433
## Week_12 158.598 1063.319 0.149 0.8851
## Week_13 704.678 1668.717 0.422 0.6839
## Week_14 2715.992 2510.458 1.082 0.3108
## Week_15 -328.866 1525.457 -0.216 0.8347
## Week_16 119.674 956.743 0.125 0.9035
## Week_17 1498.923 1047.986 1.430 0.1905
## Week_18 -1482.445 1123.229 -1.320 0.2234
## Week_19 -465.128 955.679 -0.487 0.6395
## Week_20 943.113 1047.558 0.900 0.3943
## Week_21 -148.495 1148.010 -0.129 0.9003
## Week_22 -286.892 1037.211 -0.277 0.7891
## Week_23 638.609 1018.180 0.627 0.5480
## Week_24 -992.207 890.457 -1.114 0.2975
## Week_25 1731.828 1171.769 1.478 0.1777
## Week_26 -1720.659 1175.674 -1.464 0.1815
## Week_27 2407.086 1680.372 1.432 0.1899
## Week_28 1175.362 1347.856 0.872 0.4086
## Week_29 245.021 1368.999 0.179 0.8624
## Week_30 675.510 1204.897 0.561 0.5904
## Week_31 1373.139 1103.446 1.244 0.2486
## Week_32 -115.916 655.978 -0.177 0.8641
## Week_33 -2464.103 1225.317 -2.011 0.0792 .
## Week_34 910.440 1259.533 0.723 0.4904
## Week_35 -15.881 865.415 -0.018 0.9858
## Week_36 -1366.769 1162.225 -1.176 0.2734
## Week_37 -259.754 1384.777 -0.188 0.8559
## Week_38 293.554 1249.710 0.235 0.8202
## Week_39 -12.326 1233.308 -0.010 0.9923
## Week_40 1340.438 1081.690 1.239 0.2504
## Week_41 -266.946 1272.877 -0.210 0.8391
## Week_42 840.961 1269.521 0.662 0.5263
## Week_43 1257.420 991.090 1.269 0.2402
## Week_44 -1471.160 737.609 -1.994 0.0812 .
## Week_45 -1050.131 1102.866 -0.952 0.3689
## Week_46 2202.746 1028.472 2.142 0.0646 .
## Week_47 -198.656 626.730 -0.317 0.7594
## Week_48 1264.609 1077.866 1.173 0.2744
## Week_49 355.754 566.498 0.628 0.5475
## Week_50 334.252 595.882 0.561 0.5902
## Week_51 -546.703 687.999 -0.795 0.4498
## Week_52 109.568 947.184 0.116 0.9108
## Week_53 438.117 495.110 0.885 0.4020
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5761 on 8 degrees of freedom
## Multiple R-squared: 0.9517, Adjusted R-squared: 0.632
## F-statistic: 2.976 on 53 and 8 DF, p-value: 0.05191
## [1] "Results for crop: Wheat"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3638.5 -1138.7 -64.5 1057.1 3613.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -13620.06 26181.53 -0.520 0.6170
## Week_1 -170.93 467.89 -0.365 0.7243
## Week_2 387.58 554.08 0.699 0.5041
## Week_3 -766.01 598.98 -1.279 0.2368
## Week_4 566.51 498.75 1.136 0.2889
## Week_5 -374.77 569.14 -0.658 0.5287
## Week_6 494.10 768.08 0.643 0.5380
## Week_7 359.59 626.42 0.574 0.5817
## Week_8 -433.02 995.01 -0.435 0.6749
## Week_9 361.24 546.16 0.661 0.5269
## Week_10 -1921.02 866.90 -2.216 0.0575 .
## Week_11 -1680.93 1342.49 -1.252 0.2459
## Week_12 1524.00 870.97 1.750 0.1183
## Week_13 574.84 1366.85 0.421 0.6851
## Week_14 -2024.14 2056.32 -0.984 0.3538
## Week_15 2290.80 1249.50 1.833 0.1041
## Week_16 -644.50 783.67 -0.822 0.4347
## Week_17 1634.33 858.41 1.904 0.0934 .
## Week_18 1213.25 920.04 1.319 0.2238
## Week_19 868.42 782.80 1.109 0.2995
## Week_20 972.18 858.06 1.133 0.2900
## Week_21 -585.35 940.34 -0.622 0.5509
## Week_22 460.18 849.58 0.542 0.6028
## Week_23 68.34 833.99 0.082 0.9367
## Week_24 -1212.66 729.37 -1.663 0.1350
## Week_25 -953.90 959.80 -0.994 0.3494
## Week_26 929.03 963.00 0.965 0.3629
## Week_27 794.17 1376.39 0.577 0.5798
## Week_28 634.97 1104.03 0.575 0.5810
## Week_29 -2294.68 1121.35 -2.046 0.0749 .
## Week_30 403.28 986.93 0.409 0.6935
## Week_31 689.49 903.83 0.763 0.4674
## Week_32 241.33 537.31 0.449 0.6652
## Week_33 -738.99 1003.66 -0.736 0.4826
## Week_34 3245.97 1031.68 3.146 0.0137 *
## Week_35 -597.21 708.86 -0.842 0.4240
## Week_36 -692.89 951.98 -0.728 0.4875
## Week_37 -349.95 1134.27 -0.309 0.7656
## Week_38 1247.04 1023.64 1.218 0.2578
## Week_39 -1373.30 1010.20 -1.359 0.2111
## Week_40 106.14 886.01 0.120 0.9076
## Week_41 -1294.95 1042.61 -1.242 0.2494
## Week_42 530.63 1039.87 0.510 0.6236
## Week_43 222.70 811.80 0.274 0.7908
## Week_44 -66.02 604.18 -0.109 0.9157
## Week_45 -2097.31 903.36 -2.322 0.0488 *
## Week_46 1781.16 842.42 2.114 0.0674 .
## Week_47 -235.84 513.35 -0.459 0.6582
## Week_48 -616.75 882.88 -0.699 0.5046
## Week_49 -352.65 464.02 -0.760 0.4691
## Week_50 -146.35 488.09 -0.300 0.7719
## Week_51 150.73 563.54 0.267 0.7959
## Week_52 206.51 775.84 0.266 0.7968
## Week_53 -115.02 405.54 -0.284 0.7839
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4719 on 8 degrees of freedom
## Multiple R-squared: 0.9294, Adjusted R-squared: 0.4615
## F-statistic: 1.987 on 53 and 8 DF, p-value: 0.1517
## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5846.3 -1290.8 -50.8 1531.9 4371.4
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2614.52 33260.31 0.079 0.9393
## Week_1 -677.65 594.40 -1.140 0.2872
## Week_2 -459.24 703.89 -0.652 0.5324
## Week_3 -386.17 760.92 -0.507 0.6255
## Week_4 1072.94 633.59 1.693 0.1288
## Week_5 -894.85 723.02 -1.238 0.2509
## Week_6 -484.15 975.75 -0.496 0.6331
## Week_7 745.73 795.79 0.937 0.3761
## Week_8 -1011.55 1264.04 -0.800 0.4467
## Week_9 -355.68 693.82 -0.513 0.6221
## Week_10 -830.61 1101.29 -0.754 0.4723
## Week_11 816.93 1705.46 0.479 0.6448
## Week_12 1693.65 1106.45 1.531 0.1644
## Week_13 -963.66 1736.41 -0.555 0.5941
## Week_14 2934.10 2612.29 1.123 0.2939
## Week_15 -766.97 1587.34 -0.483 0.6419
## Week_16 1045.38 995.55 1.050 0.3244
## Week_17 -227.59 1090.50 -0.209 0.8399
## Week_18 -2037.50 1168.79 -1.743 0.1195
## Week_19 358.32 994.44 0.360 0.7279
## Week_20 377.12 1090.05 0.346 0.7383
## Week_21 -1059.99 1194.58 -0.887 0.4008
## Week_22 -1251.47 1079.28 -1.160 0.2797
## Week_23 37.41 1059.48 0.035 0.9727
## Week_24 706.22 926.58 0.762 0.4678
## Week_25 801.80 1219.30 0.658 0.5293
## Week_26 511.63 1223.36 0.418 0.6868
## Week_27 -71.87 1748.53 -0.041 0.9682
## Week_28 1418.16 1402.53 1.011 0.3415
## Week_29 731.50 1424.53 0.514 0.6215
## Week_30 -1858.69 1253.77 -1.482 0.1765
## Week_31 -307.74 1148.21 -0.268 0.7955
## Week_32 74.90 682.59 0.110 0.9153
## Week_33 1348.41 1275.02 1.058 0.3211
## Week_34 390.25 1310.62 0.298 0.7735
## Week_35 -1038.43 900.52 -1.153 0.2821
## Week_36 -347.90 1209.37 -0.288 0.7809
## Week_37 -122.80 1440.95 -0.085 0.9342
## Week_38 251.42 1300.40 0.193 0.8515
## Week_39 -344.60 1283.34 -0.269 0.7951
## Week_40 -416.53 1125.57 -0.370 0.7209
## Week_41 476.62 1324.51 0.360 0.7283
## Week_42 1964.90 1321.02 1.487 0.1752
## Week_43 -1325.35 1031.29 -1.285 0.2347
## Week_44 1780.50 767.53 2.320 0.0489 *
## Week_45 -1894.00 1147.60 -1.650 0.1375
## Week_46 934.35 1070.19 0.873 0.4081
## Week_47 1417.49 652.15 2.174 0.0615 .
## Week_48 -107.34 1121.59 -0.096 0.9261
## Week_49 -844.77 589.48 -1.433 0.1897
## Week_50 -468.68 620.05 -0.756 0.4714
## Week_51 252.46 715.91 0.353 0.7335
## Week_52 -1091.62 985.60 -1.108 0.3002
## Week_53 177.79 515.19 0.345 0.7389
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5994 on 8 degrees of freedom
## Multiple R-squared: 0.8805, Adjusted R-squared: 0.08847
## F-statistic: 1.112 on 53 and 8 DF, p-value: 0.4763
## [1] "Results for crop: Grapes"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11813.4 -3030.8 397.2 3226.0 12447.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 93315.0390 74777.6071 1.248 0.2474
## Week_1 -419.4469 1336.3506 -0.314 0.7616
## Week_2 -1433.2573 1582.5262 -0.906 0.3916
## Week_3 2258.2339 1710.7507 1.320 0.2233
## Week_4 472.4900 1424.4800 0.332 0.7486
## Week_5 -1146.2948 1625.5386 -0.705 0.5007
## Week_6 353.8557 2193.7364 0.161 0.8759
## Week_7 16.4335 1789.1440 0.009 0.9929
## Week_8 -1803.9206 2841.8755 -0.635 0.5433
## Week_9 -480.1525 1559.8856 -0.308 0.7661
## Week_10 -3795.2263 2475.9821 -1.533 0.1639
## Week_11 -2046.9935 3834.3045 -0.534 0.6079
## Week_12 1572.8965 2487.5815 0.632 0.5448
## Week_13 -2297.9034 3903.8791 -0.589 0.5724
## Week_14 3461.4017 5873.0915 0.589 0.5719
## Week_15 6790.4379 3568.7313 1.903 0.0936 .
## Week_16 4154.3312 2238.2517 1.856 0.1005
## Week_17 3397.8516 2451.7104 1.386 0.2032
## Week_18 -1608.5163 2627.7381 -0.612 0.5574
## Week_19 943.7657 2235.7629 0.422 0.6841
## Week_20 1668.0157 2450.7102 0.681 0.5153
## Week_21 -945.4573 2685.7118 -0.352 0.7339
## Week_22 0.7152 2426.5036 0.000 0.9998
## Week_23 -1077.3680 2381.9820 -0.452 0.6631
## Week_24 -3291.8970 2083.1794 -1.580 0.1527
## Week_25 -3647.3402 2741.2940 -1.331 0.2200
## Week_26 4181.3355 2750.4315 1.520 0.1669
## Week_27 2963.2074 3931.1454 0.754 0.4726
## Week_28 1390.0122 3153.2425 0.441 0.6710
## Week_29 400.7122 3202.7046 0.125 0.9035
## Week_30 -1383.8310 2818.7972 -0.491 0.6367
## Week_31 -3047.3280 2581.4560 -1.180 0.2717
## Week_32 528.0668 1534.6270 0.344 0.7396
## Week_33 -808.6604 2866.5675 -0.282 0.7850
## Week_34 6494.5491 2946.6155 2.204 0.0586 .
## Week_35 1495.1868 2024.5950 0.739 0.4813
## Week_36 -128.2266 2718.9666 -0.047 0.9635
## Week_37 -5400.3101 3239.6164 -1.667 0.1341
## Week_38 4013.8240 2923.6343 1.373 0.2070
## Week_39 -6848.5002 2885.2634 -2.374 0.0450 *
## Week_40 350.0976 2530.5603 0.138 0.8934
## Week_41 -2519.6301 2977.8319 -0.846 0.4221
## Week_42 -677.9038 2969.9809 -0.228 0.8252
## Week_43 -5285.3740 2318.6053 -2.280 0.0521 .
## Week_44 -552.8590 1725.5989 -0.320 0.7569
## Week_45 -6062.1221 2580.1004 -2.350 0.0467 *
## Week_46 3191.7414 2406.0598 1.327 0.2213
## Week_47 -176.6592 1466.2031 -0.120 0.9071
## Week_48 1510.4028 2521.6136 0.599 0.5658
## Week_49 743.4374 1325.2938 0.561 0.5902
## Week_50 2045.2262 1394.0358 1.467 0.1805
## Week_51 -1932.5901 1609.5402 -1.201 0.2642
## Week_52 4028.7597 2215.8892 1.818 0.1066
## Week_53 -2245.1934 1158.2854 -1.938 0.0886 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13480 on 8 degrees of freedom
## Multiple R-squared: 0.9119, Adjusted R-squared: 0.3282
## F-statistic: 1.562 on 53 and 8 DF, p-value: 0.2595
## [1] "Results for crop: Raspberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9762.3 -2100.8 230.9 2349.8 6195.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -61187.71 46168.70 -1.325 0.2217
## Week_1 1141.71 825.08 1.384 0.2038
## Week_2 2571.75 977.07 2.632 0.0301 *
## Week_3 -481.87 1056.24 -0.456 0.6604
## Week_4 -107.62 879.49 -0.122 0.9056
## Week_5 -212.14 1003.63 -0.211 0.8379
## Week_6 -450.96 1354.44 -0.333 0.7477
## Week_7 1304.39 1104.64 1.181 0.2716
## Week_8 1800.95 1754.61 1.026 0.3347
## Week_9 -1167.50 963.09 -1.212 0.2600
## Week_10 1605.93 1528.70 1.051 0.3242
## Week_11 -2342.20 2367.35 -0.989 0.3515
## Week_12 -2007.14 1535.87 -1.307 0.2276
## Week_13 1166.39 2410.31 0.484 0.6414
## Week_14 4030.56 3626.13 1.112 0.2986
## Week_15 193.04 2203.38 0.088 0.9323
## Week_16 1030.72 1381.93 0.746 0.4771
## Week_17 577.82 1513.72 0.382 0.7126
## Week_18 1907.75 1622.40 1.176 0.2734
## Week_19 513.95 1380.39 0.372 0.7193
## Week_20 -1281.64 1513.10 -0.847 0.4216
## Week_21 4363.44 1658.19 2.631 0.0301 *
## Week_22 41.49 1498.16 0.028 0.9786
## Week_23 -2198.68 1470.67 -1.495 0.1733
## Week_24 1860.18 1286.18 1.446 0.1861
## Week_25 966.42 1692.51 0.571 0.5837
## Week_26 -1731.03 1698.15 -1.019 0.3379
## Week_27 2733.47 2427.14 1.126 0.2927
## Week_28 -3773.68 1946.85 -1.938 0.0886 .
## Week_29 556.91 1977.39 0.282 0.7854
## Week_30 1876.28 1740.36 1.078 0.3124
## Week_31 369.58 1593.83 0.232 0.8225
## Week_32 -600.33 947.50 -0.634 0.5440
## Week_33 -2804.78 1769.86 -1.585 0.1517
## Week_34 2074.56 1819.28 1.140 0.2871
## Week_35 -2122.18 1250.01 -1.698 0.1280
## Week_36 3432.87 1678.73 2.045 0.0751 .
## Week_37 1239.02 2000.18 0.619 0.5528
## Week_38 -2025.65 1805.09 -1.122 0.2943
## Week_39 -790.84 1781.40 -0.444 0.6688
## Week_40 1590.43 1562.40 1.018 0.3385
## Week_41 -368.28 1838.55 -0.200 0.8462
## Week_42 451.98 1833.71 0.246 0.8115
## Week_43 -110.83 1431.54 -0.077 0.9402
## Week_44 -907.94 1065.41 -0.852 0.4189
## Week_45 -646.03 1592.99 -0.406 0.6957
## Week_46 -1443.39 1485.53 -0.972 0.3597
## Week_47 -904.31 905.25 -0.999 0.3471
## Week_48 1098.79 1556.88 0.706 0.5004
## Week_49 1208.57 818.25 1.477 0.1779
## Week_50 -1014.99 860.70 -1.179 0.2722
## Week_51 -2542.57 993.75 -2.559 0.0337 *
## Week_52 2863.56 1368.12 2.093 0.0697 .
## Week_53 -1253.87 715.14 -1.753 0.1176
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8321 on 8 degrees of freedom
## Multiple R-squared: 0.9006, Adjusted R-squared: 0.242
## F-statistic: 1.368 on 53 and 8 DF, p-value: 0.3366
## [1] "Results for crop: Strawberries"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -8816 -2698 765 2981 9094
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -43671.26 62465.98 -0.699 0.5043
## Week_1 102.83 1116.33 0.092 0.9289
## Week_2 91.01 1321.97 0.069 0.9468
## Week_3 977.08 1429.09 0.684 0.5135
## Week_4 642.01 1189.95 0.540 0.6042
## Week_5 -1503.25 1357.90 -1.107 0.3005
## Week_6 1684.53 1832.55 0.919 0.3849
## Week_7 663.88 1494.57 0.444 0.6687
## Week_8 -2254.98 2373.98 -0.950 0.3700
## Week_9 -233.27 1303.06 -0.179 0.8624
## Week_10 -4874.81 2068.33 -2.357 0.0462 *
## Week_11 -3311.42 3203.01 -1.034 0.3314
## Week_12 2091.01 2078.02 1.006 0.3438
## Week_13 586.76 3261.13 0.180 0.8617
## Week_14 -1237.21 4906.13 -0.252 0.8073
## Week_15 5846.04 2981.16 1.961 0.0855 .
## Week_16 1960.95 1869.74 1.049 0.3249
## Week_17 4846.62 2048.05 2.366 0.0455 *
## Week_18 -99.77 2195.10 -0.045 0.9649
## Week_19 2500.27 1867.66 1.339 0.2175
## Week_20 2429.33 2047.22 1.187 0.2694
## Week_21 -1966.57 2243.53 -0.877 0.4063
## Week_22 1595.38 2027.00 0.787 0.4539
## Week_23 -1397.62 1989.80 -0.702 0.5024
## Week_24 -3222.90 1740.20 -1.852 0.1012
## Week_25 -1082.16 2289.96 -0.473 0.6491
## Week_26 3451.49 2297.59 1.502 0.1714
## Week_27 1871.65 3283.91 0.570 0.5844
## Week_28 3016.32 2634.08 1.145 0.2853
## Week_29 -4239.79 2675.40 -1.585 0.1517
## Week_30 -730.59 2354.70 -0.310 0.7643
## Week_31 1496.45 2156.44 0.694 0.5074
## Week_32 -186.27 1281.96 -0.145 0.8881
## Week_33 -2601.00 2394.61 -1.086 0.3090
## Week_34 7501.91 2461.48 3.048 0.0159 *
## Week_35 71.91 1691.26 0.043 0.9671
## Week_36 -1000.53 2271.31 -0.441 0.6712
## Week_37 -2196.19 2706.24 -0.812 0.4405
## Week_38 2494.36 2442.28 1.021 0.3370
## Week_39 -5213.91 2410.22 -2.163 0.0625 .
## Week_40 3049.40 2113.92 1.443 0.1871
## Week_41 -4397.99 2487.55 -1.768 0.1150
## Week_42 1467.46 2480.99 0.591 0.5705
## Week_43 -1320.41 1936.86 -0.682 0.5147
## Week_44 -72.22 1441.49 -0.050 0.9613
## Week_45 -6995.59 2155.30 -3.246 0.0118 *
## Week_46 4763.70 2009.92 2.370 0.0452 *
## Week_47 429.47 1224.80 0.351 0.7349
## Week_48 -329.09 2106.45 -0.156 0.8797
## Week_49 128.17 1107.09 0.116 0.9107
## Week_50 -26.66 1164.52 -0.023 0.9823
## Week_51 -454.82 1344.54 -0.338 0.7439
## Week_52 2203.10 1851.06 1.190 0.2681
## Week_53 -1115.07 967.58 -1.152 0.2824
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 11260 on 8 degrees of freedom
## Multiple R-squared: 0.957, Adjusted R-squared: 0.6718
## F-statistic: 3.356 on 53 and 8 DF, p-value: 0.03649
## # A tibble: 6 × 3
## Crop_Type Start_Year End_Year
## <chr> <int> <int>
## 1 Barley 1991 2023
## 2 Canola 1991 2023
## 3 Oats 1991 2023
## 4 Peas, dry 1991 2023
## 5 Rye, fall remaining 1991 2023
## 6 Wheat, spring 1991 2023
Part 4: new crop data
4.1:field crop data
yield
total production
total Cultivated area
4.2:fruits data
year range
## # A tibble: 39 × 4
## # Groups: Estimates [3]
## Estimates Crop_Type Start_Year
## <chr> <chr> <int>
## 1 Marketed production Fresh apples [114114111] 1926
## 2 Marketed production Fresh blueberries [1141114] 1926
## 3 Marketed production Fresh grapes [1141147] 1926
## 4 Marketed production Fresh peaches [114114411] 1926
## 5 Marketed production Fresh pears [114114211] 1926
## 6 Marketed production Fresh plums and prune plums [1141143] 1926
## 7 Marketed production Fresh raspberries [114111211] 1926
## 8 Marketed production Fresh strawberries [114111111] 1926
## 9 Cultivated area, total Fresh apples [114114111] 2002
## 10 Cultivated area, total Fresh blueberries [1141114] 2002
## 11 Cultivated area, total Fresh grapes [1141147] 2002
## 12 Cultivated area, total Fresh nectarines [114114421] 2002
## 13 Cultivated area, total Fresh peaches [114114411] 2002
## 14 Cultivated area, total Fresh pears [114114211] 2002
## 15 Cultivated area, total Fresh plums and prune plums [1141143] 2002
## 16 Cultivated area, total Fresh raspberries [114111211] 2002
## 17 Cultivated area, total Fresh strawberries [114111111] 2002
## 18 Marketed production Fresh nectarines [114114421] 2002
## 19 Cultivated area, total Fresh apricots [114114431] 2007
## 20 Cultivated area, total Fresh cranberries [114111311] 2007
## 21 Cultivated area, total Fresh sour cherries [114114521] 2007
## 22 Cultivated area, total Fresh sweet cherries [114114511] 2007
## 23 Marketed production Fresh apricots [114114431] 2007
## 24 Marketed production Fresh cranberries [114111311] 2007
## 25 Marketed production Fresh sour cherries [114114521] 2007
## 26 Marketed production Fresh sweet cherries [114114511] 2007
## 27 Total production Fresh apples [114114111] 2011
## 28 Total production Fresh apricots [114114431] 2011
## 29 Total production Fresh blueberries [1141114] 2011
## 30 Total production Fresh cranberries [114111311] 2011
## 31 Total production Fresh grapes [1141147] 2011
## 32 Total production Fresh nectarines [114114421] 2011
## 33 Total production Fresh peaches [114114411] 2011
## 34 Total production Fresh pears [114114211] 2011
## 35 Total production Fresh plums and prune plums [1141143] 2011
## 36 Total production Fresh raspberries [114111211] 2011
## 37 Total production Fresh sour cherries [114114521] 2011
## 38 Total production Fresh strawberries [114111111] 2011
## 39 Total production Fresh sweet cherries [114114511] 2011
## End_Year
## <int>
## 1 2023
## 2 2023
## 3 2023
## 4 2023
## 5 2023
## 6 2023
## 7 2023
## 8 2023
## 9 2023
## 10 2023
## 11 2023
## 12 2023
## 13 2023
## 14 2023
## 15 2023
## 16 2023
## 17 2023
## 18 2023
## 19 2023
## 20 2023
## 21 2023
## 22 2023
## 23 2023
## 24 2023
## 25 2023
## 26 2023
## 27 2023
## 28 2023
## 29 2023
## 30 2023
## 31 2023
## 32 2023
## 33 2023
## 34 2023
## 35 2023
## 36 2023
## 37 2023
## 38 2023
## 39 2023
Yield (kilograms per hectare)
Marketed production (ton)
total Cultivated area (Hectares)
fill area with mean
mean as previous value
calculate the yield again
individual crop yield
4.3: lm with crop 1990-2024
FortStJohn monthly for Peace River region
## [1] "There are 5 NA in the matrix X in FortStJoh station"
## [1] "Results for crop: Barley"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -810.77 -210.13 -45.77 216.09 876.48
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2747.565 132.603 20.720 5.49e-15 ***
## Month_1 3.671 3.271 1.122 0.27511
## Month_2 -1.625 5.889 -0.276 0.78550
## Month_3 -10.737 6.665 -1.611 0.12288
## Month_4 -21.387 5.908 -3.620 0.00171 **
## Month_5 27.866 8.546 3.261 0.00391 **
## Month_6 -5.543 4.113 -1.348 0.19282
## Month_7 -16.804 9.772 -1.720 0.10094
## Month_8 -15.634 20.745 -0.754 0.45987
## Month_9 -34.634 18.477 -1.874 0.07555 .
## Month_10 -46.651 33.615 -1.388 0.18047
## Month_11 10.350 8.267 1.252 0.22500
## Month_12 0.548 4.713 0.116 0.90859
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 442.6 on 20 degrees of freedom
## Multiple R-squared: 0.6662, Adjusted R-squared: 0.466
## F-statistic: 3.327 on 12 and 20 DF, p-value: 0.008594
## [1] "Results for crop: Canola"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -495.78 -201.82 -22.08 224.12 494.01
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.640e+03 1.049e+02 15.627 1.13e-12 ***
## Month_1 8.420e-01 2.588e+00 0.325 0.74832
## Month_2 -3.685e-01 4.660e+00 -0.079 0.93776
## Month_3 -2.422e+00 5.274e+00 -0.459 0.65100
## Month_4 3.546e-01 4.674e+00 0.076 0.94028
## Month_5 2.033e+01 6.762e+00 3.007 0.00697 **
## Month_6 4.823e-03 3.254e+00 0.001 0.99883
## Month_7 1.363e+01 7.732e+00 1.763 0.09316 .
## Month_8 -3.024e+01 1.641e+01 -1.842 0.08030 .
## Month_9 -9.163e+00 1.462e+01 -0.627 0.53789
## Month_10 9.810e+00 2.660e+01 0.369 0.71614
## Month_11 2.620e+00 6.541e+00 0.401 0.69294
## Month_12 2.417e+00 3.729e+00 0.648 0.52432
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 350.2 on 20 degrees of freedom
## Multiple R-squared: 0.5118, Adjusted R-squared: 0.2189
## F-statistic: 1.748 on 12 and 20 DF, p-value: 0.1302
## [1] "Results for crop: Oats"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -686.30 -298.04 14.58 346.99 723.26
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2594.6436 152.9915 16.959 2.45e-13 ***
## Month_1 6.9024 3.7741 1.829 0.08236 .
## Month_2 -6.6119 6.7945 -0.973 0.34211
## Month_3 0.7560 7.6902 0.098 0.92267
## Month_4 -13.0867 6.8161 -1.920 0.06924 .
## Month_5 30.1494 9.8599 3.058 0.00621 **
## Month_6 2.8667 4.7455 0.604 0.55257
## Month_7 -13.1842 11.2744 -1.169 0.25599
## Month_8 -20.3265 23.9352 -0.849 0.40581
## Month_9 -8.4361 21.3175 -0.396 0.69649
## Month_10 -45.3332 38.7836 -1.169 0.25620
## Month_11 0.5282 9.5375 0.055 0.95638
## Month_12 6.9356 5.4377 1.275 0.21676
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 510.6 on 20 degrees of freedom
## Multiple R-squared: 0.5482, Adjusted R-squared: 0.2772
## F-statistic: 2.023 on 12 and 20 DF, p-value: 0.07897
## [1] "Results for crop: Peas, dry"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -587.52 -153.37 4.09 172.14 555.40
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2283.3846 106.2762 21.485 2.74e-15 ***
## Month_1 0.4053 2.6217 0.155 0.8787
## Month_2 4.8273 4.7198 1.023 0.3186
## Month_3 7.8679 5.3420 1.473 0.1564
## Month_4 -9.8101 4.7348 -2.072 0.0514 .
## Month_5 9.9292 6.8493 1.450 0.1627
## Month_6 -2.0050 3.2965 -0.608 0.5499
## Month_7 -18.6597 7.8318 -2.383 0.0272 *
## Month_8 -27.2808 16.6267 -1.641 0.1165
## Month_9 -18.9174 14.8083 -1.277 0.2161
## Month_10 22.9643 26.9412 0.852 0.4041
## Month_11 5.6301 6.6252 0.850 0.4055
## Month_12 -1.0693 3.7773 -0.283 0.7800
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 354.7 on 20 degrees of freedom
## Multiple R-squared: 0.632, Adjusted R-squared: 0.4112
## F-statistic: 2.863 on 12 and 20 DF, p-value: 0.01824
## [1] "Results for crop: Rye, fall remaining"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -332.65 -101.24 -16.46 128.25 327.91
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2918.466 69.585 41.941 < 2e-16 ***
## Month_1 -5.645 1.717 -3.288 0.00367 **
## Month_2 -11.845 3.090 -3.833 0.00104 **
## Month_3 -8.053 3.498 -2.302 0.03219 *
## Month_4 -2.919 3.100 -0.942 0.35765
## Month_5 1.866 4.485 0.416 0.68170
## Month_6 -4.689 2.158 -2.172 0.04202 *
## Month_7 6.813 5.128 1.329 0.19895
## Month_8 -12.300 10.886 -1.130 0.27190
## Month_9 2.846 9.696 0.294 0.77216
## Month_10 -21.121 17.640 -1.197 0.24516
## Month_11 10.945 4.338 2.523 0.02021 *
## Month_12 1.048 2.473 0.424 0.67638
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 232.3 on 20 degrees of freedom
## Multiple R-squared: 0.8199, Adjusted R-squared: 0.7118
## F-statistic: 7.588 on 12 and 20 DF, p-value: 4.424e-05
## [1] "Results for crop: Wheat, spring"
##
## Call:
## lm(formula = y ~ ., data = x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -956.43 -258.19 -44.64 364.59 696.77
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2734.4157 165.1893 16.553 3.86e-13 ***
## Month_1 -0.1194 4.0750 -0.029 0.97692
## Month_2 -5.4679 7.3362 -0.745 0.46474
## Month_3 6.0417 8.3033 0.728 0.47528
## Month_4 -22.9612 7.3595 -3.120 0.00540 **
## Month_5 30.8880 10.6461 2.901 0.00883 **
## Month_6 -1.6546 5.1238 -0.323 0.75011
## Month_7 -29.6905 12.1732 -2.439 0.02417 *
## Month_8 -5.4537 25.8436 -0.211 0.83500
## Month_9 12.9619 23.0171 0.563 0.57960
## Month_10 -42.4457 41.8757 -1.014 0.32287
## Month_11 -12.2600 10.2979 -1.191 0.24777
## Month_12 3.6215 5.8713 0.617 0.54431
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 551.4 on 20 degrees of freedom
## Multiple R-squared: 0.6203, Adjusted R-squared: 0.3925
## F-statistic: 2.723 on 12 and 20 DF, p-value: 0.02309
Part 5: veg data
## # A tibble: 322 × 4
## # Groups: Crop_Type [34]
## Crop_Type Estimates Start_Year End_Year
## <chr> <chr> <int> <int>
## 1 Brussels sprouts Area harvested (acres) 2007 2023
## 2 Brussels sprouts Area harvested (hectares) 2007 2023
## 3 Brussels sprouts Area planted (acres) 2007 2023
## 4 Brussels sprouts Area planted (hectares) 2007 2023
## 5 Brussels sprouts Average yield per acre (pounds) 2007 2017
## 6 Brussels sprouts Average yield per hectare (kilograms) 2007 2017
## 7 Brussels sprouts Marketed production (metric tonnes) 2007 2023
## 8 Brussels sprouts Marketed production (tons) 2007 2023
## 9 Brussels sprouts Total production (metric tonnes) 2007 2023
## 10 Brussels sprouts Total production (tons) 2007 2023
## # ℹ 312 more rows
## # A tibble: 140 × 4
## # Groups: Crop_Type [14]
## Crop_Type Estimates Start_Year End_Year
## <chr> <chr> <int> <int>
## 1 asparagus Area harvested (acres) 1982 2023
## 2 asparagus Area harvested (hectares) 2002 2023
## 3 asparagus Area planted (acres) 1940 2023
## 4 asparagus Area planted (hectares) 2002 2023
## 5 asparagus Average yield per acre (pounds) 1940 2017
## 6 asparagus Average yield per hectare (kilograms) 2002 2017
## 7 asparagus Marketed production (metric tonnes) 2002 2023
## 8 asparagus Marketed production (tons) 1982 2023
## 9 asparagus Total production (metric tonnes) 2002 2023
## 10 asparagus Total production (tons) 1940 2023
## # ℹ 130 more rows
plot good quality replacement for yield data
plot ok quality replacement for yield data
plot soso quality replacement for yield data
plot mixed quality replacement for yield data
plot bad quality replacement for yield data
